Large Language Models | Field

Lead research scientist at Ai2 and a founding member of the OLMo team. He works on open language models, language agents, evaluation, and reasoning, and helps build open-model research infrastructure.

Senior research scientist at Ai2 working on natural language processing, machine learning, and reasoning for the Aristo project; previously a researcher at the Institute for Natural Language Processing at the University of Stuttgart.

Yukun Zha is a research scientist at DeepSeek. His public profile lists research interests in machine learning, reinforcement learning, and efficient inference, alongside a PhD in computer science from Dartmouth College.

Computer scientist, UC Berkeley professor, and Databricks co-founder and CTO. He created Apache Spark and works on systems for large-scale data, machine learning, and compound AI applications.

PhD student at the University of Washington advised by Luke Zettlemoyer and researcher at Ai2. His work focuses on open language models, instruction tuning, data curation, and evaluation.

OpenAI researcher whose work spans alignment, machine learning, complexity science, open-ended evolution, and artificial life.

OpenAI researcher and engineer working on LLM reasoning; previously at Meta AI, DeepMind, and Jane Street.

AI researcher who co-created Sora at OpenAI and invented InstructPix2Pix during his PhD at Berkeley AI Research.

Research scientist at Tongyi Lab, Alibaba Group, working on multimodal large language models, machine reasoning, and efficient learning.

Research scientist at NVIDIA and University of Maryland PhD student whose public site highlights speech, audio, and video generation plus alignment for large language and vision-language models.

PhD student at the University of Chinese Academy of Sciences and researcher at BIGAI focused on reasoning, long context, and diffusion models; previously interned at DeepSeek, Microsoft Research Asia, and IDEA Research.

Junyang Lin (Justin Lin) is a researcher and open-source maintainer known for the Qwen family of models. His public profiles list interests in LLMs, AI agents, multimodal learning, long-horizon reasoning, world models, and reinforcement learning; multiple March 2026 news reports said he stepped down from the Qwen tech lead role.

Pradeep Dasigi is a senior research scientist at NVIDIA. His public profile notes previous work at the Allen Institute for AI and a PhD in computer science from the University of Pennsylvania, with research spanning NLP, semantic parsing, and knowledge graphs.

Senior applied scientist at NVIDIA working on open foundation models and post-training. Previously he was a visiting researcher at Google DeepMind and Google Brain, and he earned an MSc in computer science from ETH Zurich.

Researcher at Anthropic working on machine learning, language models, and reinforcement learning. Previously a postdoctoral researcher at Meta FAIR, and he earned a PhD in computer science from Harvard University.

Ilge Akkaya is a research scientist at OpenAI working on reinforcement learning and robotics. His personal website lists a PhD in EECS from UC Berkeley and a BS in Electrical and Electronics Engineering from Bilkent University.

Zihan Wang is a Northwestern University PhD candidate advised by Manling Li whose research focuses on agentic reinforcement learning, model efficiency, and long-context understanding. His official homepage lists prior internships at DeepSeek, Microsoft, and Yutori.

Engineer and product leader who worked on OpenAI's Applied AI team and now advises startups on AI products. He writes publicly about agents, retrieval, and evaluation on his personal site.

Algorithm Engineer at the Qwen Team, Alibaba Group. He received his Ph.D. in computer science from Beihang University in 2024 and works on post-training alignment for Qwen models, with research interests in large language models, graph neural networks, and recommender systems.

PhD student at Renmin University of China whose homepage highlights multimodal foundation models and video understanding, with public projects and papers including DeepSeek-VL and Kimi-VL.

Adria Garriga-Alonso is a research scientist at Google DeepMind focused on machine learning and AI safety. His public profile notes a PhD in computer science from the University of Cambridge in 2020.

Research scientist at OpenAI working on AI agents, large models, and reinforcement learning. Previously worked as an applied scientist at Uber and completed a PhD in computer science at ENS Paris-Saclay under Marc Schoenauer and Olivier Teytaud.

Postdoctoral researcher at the Allen Institute for AI and the University of Washington whose work focuses on open language model post-training, steerability, and evaluation.

Research scientist at Google Research in New York City. He earned a PhD in computer science from NYU Tandon and works on language models, multimodal learning, NLP, and deep learning.

Research scientist in Tongyi Lab whose official profile highlights large language models, multimodal foundation models, and AI agents.

Xin Hu is a Member of Technical Staff at OpenAI focused on privacy and security. Xin previously held cybersecurity and machine learning roles at Robinhood, Pinterest, IBM Research, and Intel, and earned a PhD in Computer Science and Engineering from the University of Michigan.

Bowen Yu is an Algorithm Expert at Qwen (Alibaba Group) working on LLM post-training and automated alignment.

Research scientist at OpenAI working on intelligent agents, computer vision, natural language processing, and robotics; he previously completed a PhD in computer science at Penn State.

Researcher working on machine learning systems and infrastructure at OpenAI. He earned his PhD from UCLA.

AI safety researcher and engineer; former OpenAI employee, founder and AI advisor at Metaculus, and creator of the CosmoTransitions package.

Research scientist at Moonshot AI studying scaling in reinforcement learning and large language models.

Research scientist at NVIDIA working on compression, efficient inference, post-training, multimodality, and evaluation for large language models. He completed a PhD in machine learning at Stanford and a master's in artificial intelligence at the University of Edinburgh.

Research scientist at OpenAI whose public profiles highlight multi-agent alignment, scalable training, and reinforcement learning.

Leon Derczynski is a professor in natural language processing at DTU Compute whose research focuses on information extraction, online harms, and the dynamics of abusive language and misinformation.

Resident at xAI and long-term visitor at the Center for AI Safety. He recently completed a PhD in electrical and computer engineering at the University of Texas at Austin, and his work is grounded in mathematical and statistical machine learning plus control theory.

Juntang Zhuang is a research scientist at OpenAI working on multimodal learning and diffusion models. His public profile notes a PhD in computer science from UC Berkeley and earlier research internships at Google DeepMind and Microsoft.

Yufei Guo is an assistant professor in the UCLA Computer Science Department. His public profiles note prior work as a research scientist at OpenAI and research interests in AI agents, reinforcement learning, and large language models.

Member of technical staff at OpenAI working on alignment. Previously worked at Google, DeepMind, and Meta, and completed a PhD in neuroscience at Oxford.

Head of AI at Cohere and professor at the University of Pennsylvania whose public profiles focus on natural language understanding, reasoning, and grounding.

Research scientist at Google DeepMind working on trustworthy deep learning, multimodal modeling, and generalization in AI systems.

Mitesh M. Khapra is a professor at IIT Madras and co-founder of AI4Bharat whose research spans natural language processing, machine learning, transfer learning, and deep learning.

Trung H. Bui is a staff researcher at Cohere working on generative AI, large language models, natural language processing, machine learning, and computer vision.

Alec Radford is a researcher and a co-author of the GPT-4 Technical Report. His GitHub profile links to his personal website at newmu.github.io.

Seungyoun Hong is a research scientist and postdoctoral scholar at Stanford University working on machine unlearning, data attribution, hallucination, and generalization.

Assistant professor in the University of Pennsylvania Department of Computer and Information Science whose research spans natural language processing, speech, and multimodal learning; previously a research scientist at Facebook AI Research.

Research scientist at Cohere Labs and PhD candidate at Stanford University focused on language models, machine learning systems, and AI safety.

Technical staff member at OpenAI working on large language models. Previously worked on Siri at Apple, and graduated from Carnegie Mellon University.

Senior algorithm expert at Alibaba Group working on large language models, multimodal large language models, and diffusion models.

Joshua (Josh) Achiam is Chief Futurist at OpenAI. He joined OpenAI in 2017 as a research scientist and has worked on AI safety research and operations, AI impacts research, and educational resources (including Spinning Up in Deep RL).

Research scientist at AI2; previously a machine learning engineer at Koko, where he worked on safety systems for language models.

Research scientist at Google DeepMind interested in efficient and reliable language models, reasoning, and model security. His personal site also highlights prior work on planning, geometry, and representation learning.

Boris Ginsburg is a principal engineer and research scientist at NVIDIA whose work focuses on efficient machine learning and deep learning for speech recognition, language processing, and computer vision.

Sebastian Gehrmann is a staff research scientist at Mistral AI working on language generation, information extraction, and the evaluation of generative systems.

Amelie Haghighat is an incoming assistant professor at the University of Illinois Chicago whose research focuses on trustworthy and resource-efficient machine learning systems.

Ana Klimovic is an assistant professor of computer science at ETH Zurich whose research focuses on machine learning systems, efficient hardware acceleration, and sustainable AI.

Compiler researcher and entrepreneur, creator of the PolyMage DSL, and Professor at the Indian Institute of Science whose work spans compilers, AI systems, and programming languages.

Research scientist at Meta GenAI working on efficient and safe language and multimodal systems. She completed a Ph.D. in computer science at Carnegie Mellon University.

Researcher at DeepSeek whose public homepage describes work on DeepSeek R1, V1, V2, V3, Math, Coder, and mixture-of-experts systems.

Researcher at Moonshot AI working on multimodal large language models; previously a key member of Alibaba's Qwen team and author of work including Kimi-VL, DeepSeek-VL, and Qwen technical reports.

Yizhong Wang is a research scientist at the Allen Institute for AI and incoming assistant professor at the University of Washington whose work focuses on language models, agents, reasoning, and open-source AI.

Thomas B. Brown is a research scientist at Google DeepMind whose work focuses on language models, multimodality, and reasoning.

Boris Ivanovic is a postdoctoral scholar in Stanford's Autonomous Systems Lab whose research focuses on human-centered machine learning and data-driven prediction and planning for autonomous systems.

Geri Skenderi is a research scientist at Cohere focusing on multilingual language technology, evaluation of large language models, and natural language processing for low-resource settings.

Research scientist at Meta FAIR focused on computer vision and multimodal understanding, including image and video models, visual reasoning, large-scale training, and evaluation.

Research scientist at Meta AI working on natural language processing, dialogue systems, and large language models.

Algorithm expert at Alibaba DAMO Academy focused on natural language generation and large language models.

Yichang Zhang is a research scientist in Alibaba's Tongyi Lab and part of the Qwen team. His public profiles describe work on machine reasoning, agent systems, post-training, synthetic data, evaluation, large language models, multimodal learning, and perception.

Yuling Gu is a PhD student at the NYU Center for Data Science studying large language models, machine reasoning, and robust evaluation. She was previously a predoctoral researcher at the Allen Institute for AI, where she contributed to OLMo, OLMo 2, OLMo 3, TULU 3, OLMoE, and OLMES.

Aakanksha Chowdhery is a machine learning researcher based in New York City. She works on large-scale machine learning across pre-training, post-training, inference, and system efficiency, and is known for contributions such as PaLM, Pathways, and Gemini.

AI researcher focused on reasoning and agents who worked on GPT-4, o1, and Deep Research; previously at Google Brain and earned a PhD at MIT.

Researcher at DeepSeek AI focusing on multimodal large language models and multimodal understanding.

Steven Adler is a former OpenAI safety researcher and technical program manager (2020-2024). He writes Clear-Eyed AI, analyzing AI news, policy, and research with a focus on risk reduction.

Wangding Zeng is a researcher at DeepSeek. His OpenReview profile also lists graduate and undergraduate study at Beijing University of Posts and Telecommunications.

Ameet Talwalkar is an associate professor in the Machine Learning Department at Carnegie Mellon University and Chief Scientist at Datadog. His public research spans AI for science, human-AI interaction, and specialized models and agents.

Researcher at Thinking Machines, formerly at OpenAI, working on real-time multimodal systems across language, vision, and voice.

Research leader at Google DeepMind and Google Research focused on natural language processing and machine learning, including large language models such as PaLM and Gemini.

Yuntian Deng is a machine learning researcher whose public work spans language modeling, reasoning, and large multimodal systems.

Research scientist focused on deep learning and large language models. He has worked at Google DeepMind, Meta, OpenAI, and Google Brain, and earned a PhD from UMass Amherst.

Brian Lester is a Senior Research Engineer at Google working on natural language processing and efficient ways to adapt large pre-trained language models. His public work includes prompt tuning, SPoT, and FLAN-related research.

Chunlin Li is a research scientist at MiniMax.

AI researcher focused on evaluating language models and agents, open NLP research, and historical linguistics. She led evaluation efforts at Hugging Face between 2023 and 2025 and helped build LightEval and the Open LLM Leaderboard.

Ai2 engineer whose public GitHub and Hugging Face profiles describe him as building LLMs at Ai2; he is also listed on OpenReview as an OLMo author.

Research scientist at Ai2 focused on language models, evaluation, and AI safety. Her work studies reasoning, truthfulness, and how to make large models more reliable.

OpenAI engineer focused on GPU systems and large-model infrastructure, with public contributions to GPT-4 and earlier OpenAI research on efficient GPU kernels and code models.

Research Scientist on the Qwen team at Alibaba Cloud.

Sandhini Agarwal is a researcher at OpenAI. Her OpenReview profile lists her as a researcher at OpenAI (2020–present) and an undergraduate student at Stanford University (2015–2019).

Chuanqi Tan works on LLM research and applications. His personal homepage says he earned a PhD from Tsinghua University in 2019 and is also a postdoctoral fellow at The University of Hong Kong.

Assistant professor at the University of Oxford and research scientist at NVIDIA. His public work focuses on robot learning, robotics, reinforcement learning, computer vision, and multimodal models.

Research scientist at OpenAI working on generative models and world models; previously at Mila and Meta AI, with a PhD from Universite de Montreal.

Software engineer focused on developer tools, infrastructure, and AI products. He has worked at OpenAI in San Francisco and publishes engineering projects and writing on his website and GitHub.

Research scientist at OpenAI focused on deep learning for science and autoregressive sequence modeling. Previously worked at MPI for Intelligent Systems, Microsoft Research, and the University of Amsterdam.

MPhil student in the Department of Computer Science and Engineering at HKUST interested in LLM agents and multimodal models; previously interned with the DeepSeek LLM Alignment Team.

Designer focused on brands, websites, and creative tools. He helped grow design at OpenAI from 0 to 1 and later joined Cursor.

Michelle Pokrass is an OpenAI researcher working on multimodal AI, especially speech and audio. Her public profiles also show work on ChatGPT and model releases including GPT-4.1.

Co-founder and CEO of Ideogram and former senior staff research scientist at Google Brain in Toronto. He is known for work on generative models and representation learning, including contributions to Imagen, WaveGrad, and SimCLR.

Research scientist at Cohere focused on scaling machine learning systems and improving training efficiency.

Researcher at OpenAI working on AI systems and machine learning. His personal site notes previous research work at Meta AI and a PhD in Computer Science from Carnegie Mellon University.

Ph.D. student in Computer Science at Stanford University who previously worked on LLMs and agents with Alibaba's Qwen team.

PhD student at the University of Washington and Student Researcher at Ai2 working on aligning language models and making them more useful.

Alejandro Lopez-Lira is an assistant professor of finance at the University of Florida whose research interests include investments, machine learning, and empirical asset pricing.

Alethea Power is a research scientist at OpenAI. Her personal website notes earlier PhD work at Georgia Tech and research interests spanning language, reasoning, cognitive science, and brain-inspired approaches to intelligence.

Researcher working on language models, agents, and retrieval-augmented generation; currently at xAI and incoming assistant professor at the University of Washington, previously a research scientist at the Allen Institute for AI.

Research scientist at DeepSeek interested in reinforcement learning, large language models, and reasoning.

Researcher at Alibaba's Qwen team, previously a PhD student in the CUHK Text Mining Group, working on RL for LLM reasoning and alignment.

Researcher at OpenAI on the mid-training team, previously working on post-training and reinforcement learning including WebGPT, ChatGPT with Browsing, and GPT-4.

Chujie Zheng is an incoming senior researcher at Alibaba Group. His academic homepage says he is finishing a Ph.D. at the University of Wisconsin-Madison and works on large language model reasoning, alignment, and reinforcement learning.

Research scientist at NVIDIA working on AI systems and large-scale machine learning, with research spanning distributed systems, deep learning, and networking.

Dibya Ghosh is a machine learning researcher at Cohere and a PhD student in computer science at UC Berkeley advised by Sergey Levine. His work spans reinforcement learning and large language models, with a focus on how foundation models can improve learning agents.

Machine learning researcher known for work on variational autoencoders, Adam, Glow, and variational diffusion models; his public homepage notes that he was part of OpenAI's founding team and is now at Anthropic.

Diyi Yang is an assistant professor of computer science at Stanford University. Her research focuses on natural language processing and machine learning, especially human-centered AI, social computing, and computational social science. She earned her PhD in language technologies from Carnegie Mellon University.

Emilie Grave is a research scientist at FAIR. Her research interests include representation learning, natural language processing, and machine learning.

Postdoctoral fellow at Johns Hopkins University and incoming assistant professor at UNC Chapel Hill whose work focuses on multilingual NLP, grounded language understanding, and societal impacts of language technologies.

Han Bao is a research scientist at DeepSeek AI. His homepage says he works on machine learning theory, including out-of-distribution generalization, robust machine learning, self-supervised learning, and learning-based control.

Researcher currently at Tencent Hunyuan with public work in natural language processing, structured information extraction, and large language models.

Engineer on the Qwen team at Alibaba Cloud.

Member of Technical Staff at OpenAI and co-instructor of DeepLearning.AI's ChatGPT Prompt Engineering for Developers and Building Systems with the ChatGPT API courses; listed as a co-author of the GPT-4 Technical Report.

Iz Beltagy is an NLP researcher known for work on OLMo, Longformer, SciBERT, and other open language technologies. His public profile highlights research on open language models, scientific NLP, and long-context modeling.

Research scientist focused on making powerful AI systems go well; his personal site lists research roles at Redwood Research, Google DeepMind, and NVIDIA.

PhD student at Shanghai Jiao Tong University advised by Prof. Xueqi Cheng. Her research interests include retrieval and agents, multimodal large language models, and biomedical large language models, and she is currently an intern at DeepSeek.

Lewis Tunstall is a principal scientist at Cohere Labs who works on open-source language models, evaluation, and multilingual NLP.

Researcher at DeepSeek AI and incoming Ph.D. student at the University of Hong Kong working on efficient and trustworthy LLMs, multimodal large language models, and reasoning.

Research scientist at Meta FAIR focused on multilinguality, machine translation, speech, and web-scale processing; previously a postdoctoral scholar at Stanford's Center for Research on Foundation Models.

Mingxiao Li is a machine learning researcher focused on vision-language models, generative models, and multimodal learning. His public homepage lists a PhD at KU Leuven, and public research outputs also list him with Moonshot AI Ltd. affiliation.

Machine learning researcher and engineer; contributed to the GPT-4 Technical Report; previously an MSc by Research student at the University of Oxford Department of Computer Science.

Founding member of OpenAI and vice president of product who writes publicly about building things and machine learning.

R. X. Xu is a research scientist at DeepSeek AI. His homepage says he works on trustworthy and efficient large language models, open-ended reasoning, and AI for healthcare.

Researcher at OpenAI focused on synthetic data, reinforcement learning, and data-centric methods for language models. He previously worked on Meta's LLaMA team and earned a PhD in computer science at Stanford.

Saurabh Pan is an AI researcher at FAIR Meta and a PhD student at Carnegie Mellon University. His work focuses on self-supervised learning, generative modeling, multimodal learning, and representation learning.

Research software engineer at Google DeepMind working on machine learning for code and formal reasoning; completed a PhD at TU Darmstadt on uncertainty quantification in deep learning.

Technical staff at OpenAI working on machine learning research, large language models, multimodal models, and robotics.

Software engineer at NVIDIA with public work spanning machine learning systems and large language models, including Nemotron-4.

Vijay Janapa Reddi is a professor of electrical engineering and computer science at Harvard University whose research spans computer architecture, systems, compilers, and machine learning.

Research scientist at DeepSeek interested in post-training, tool use, and in-context learning.

Wen Ouyang is a Vice President of AI at Tencent and Director of the Visual Computing Center, where he leads the Hunyuan multimodal foundation model team. His research covers computer vision, multimodal models, and visual understanding.

Assistant Professor at the NYU Courant Institute of Mathematical Sciences. He studies formal models of intelligence, including language, learning, and efficient reasoning, and previously worked as a research scientist at Ai2.

Xiang Lisa Li is a researcher focused on controllable and steerable language models. Her public profile highlights work including Diffusion-LM, Prefix-Tuning, Contrastive Decoding, and evaluation methods such as AutoBencher.

Research scientist at Cohere working on large language models; previously a postdoctoral researcher in machine learning at Carnegie Mellon University.

Zhiniu Wen is a research scientist at DeepSeek. His homepage says his research interests include natural language processing, machine learning, large language models, and their applications.

Adriana Hummel is a PhD student in computer science at Stanford University working on efficient and trustworthy AI systems.

Anjali Gupte is a PhD student in computer science at the University of Southern California whose research focuses on trustworthy AI, natural language processing, and information retrieval.

PhD candidate at the University of Washington and research scientist at Cohere working on natural language processing and machine learning.

DeepSeek researcher focused on NLP, code intelligence, and LLM reasoning, with public work spanning DeepSeek-Coder, DeepSeekMath, DeepSeek-V2, DeepSeek-V3, and DeepSeek-R1.

Jiahui Yu is a research scientist at Google DeepMind working on multimodal learning and large language models.

Co-founder and head of policy at Anthropic. He previously served as policy director at OpenAI, worked as a technology journalist, and writes the Import AI newsletter.

Noah A. Smith is a computer scientist and professor at the University of Washington, where he serves as Vice Provost for Artificial Intelligence and co-directs the OLMo open language modeling effort with Ai2. His research focuses on natural language processing, machine learning, and evaluation methodology.

Researcher at DeepSeek AI working on decision-making and post-training for large language models.

Co-founder and CEO of Mistral AI and a researcher on efficient large language models and mixture-of-experts systems.

Ching-Yao Chuang is a research scientist at NVIDIA working on computer vision, machine learning, and generative AI.

Professor at the University of Washington and Senior Director of NLP at AI2. Her work spans natural language processing, computer vision, responsible AI, and applications to science and medicine.

Xinyun Chen is a machine learning researcher at Meta FAIR. Her work spans large language models, code generation, mathematical reasoning, and efficient inference.

David Atkinson is a senior research scientist at Ai2 working on multimodal learning, document understanding, visual question answering, and natural language processing.

Peter Clark is Senior Director for AI at the Allen Institute for Artificial Intelligence (Ai2), where he works on natural language understanding, reasoning, and question answering.

Vasu Singhal is an AI researcher focused on natural language processing, generative AI, and machine learning. He studied computer science at Stanford University and has worked on NLP research at FAIR.

Research scientist in Tongyi Lab whose official profile highlights multimodal large language models, efficient reasoning, and AI infrastructure.

Suchir Balaji was a Member of Technical Staff at OpenAI (Nov 2020 to Aug 2024). His personal site states he studied Computer Science at UC Berkeley (2017 to 2021).

Stanford AI Lab PhD researcher focused on large language models, multimodal language models, and NLP; contributed to NVIDIA multimodal model work.

DeepSeek engineer and co-author of the DeepSeek-V3, DeepSeek-V2, and DeepSeek LLM technical reports.

First-year Ph.D. student in Information Engineering at the Chinese University of Hong Kong advised by Dahua Lin and Jifeng Dai. His research interests include understanding and building intelligence in multimodal large language models.

Diogo Almeida is an AI researcher and a co-author of the InstructGPT paper (arXiv:2203.02155).

Myle Ott is a research scientist at Meta working on the Llama models. His interests include scalable optimization, distributed systems, and language model pretraining.

Software engineer at OpenAI focused on inference. Previously studied computer science at Princeton University.

Machine learning researcher and PhD student at the University of Cambridge focused on multilingual and equitable NLP, especially for low-resource languages such as Filipino. He previously worked on open language model efforts at Ai2 including Tulu 3 and OLMo 2.

Researcher at OpenAI who led InstructGPT and GPT-4 post-training. He previously co-founded Merlyn Mind and was an engineering director at Quora.

Lucas Beyer is an ML researcher at Google DeepMind in Zurich. His public homepage highlights prior work at Google Brain and a PhD at ETH Zurich.

Maarten Sap is an assistant professor at the University of Washington and a senior research scientist at the Allen Institute for AI. His work focuses on human-centered language technologies and social NLP.

Researcher at Alibaba Group exploring the math and science of large language models; incoming assistant professor at Nanyang Technological University.

Nick Ryder is VP of Research, Foundations at OpenAI and a contributor to GPT-4. He previously studied mathematics at UC Berkeley and Rice University.

Senior director of natural language processing at the Allen Institute for AI and professor at the University of Washington. Her public profile highlights work in natural language processing, machine learning, computer vision, and AI ethics.

Algorithm expert at Alibaba Group working on computer vision, multimodal learning, and large language models.

Research scientist at DeepSeek with public GitHub projects on large language models and AI systems.

Irwan Bello is a research scientist working on generative models and vision-language systems. His personal site states that he is a research scientist at Google Research and that he completed a BS in Computer Science at the University of the Philippines Diliman in 2011.

Ahmad Al-Dahle is Airbnb's VP of AI. He previously founded Meta's generative AI team and helped launch the Llama models after earlier leadership work on search and Siri at Apple.

Research scientist at Ai2 working on language models and open research infrastructure. His interests include natural language processing, machine learning, and building reliable open-source systems.

Ali Payani is a Research Scientist at Google DeepMind working on natural language generation and natural language reasoning. His public research interests include reasoning, planning, and grounding with language models.

Research scientist at Thinking Machines Lab with prior language-model work at OpenAI and earlier quantitative research at Bridgewater. Her public profile highlights interests in scaling language models, new architectures, and adaptive inference.

Braden Hancock is a researcher at Google DeepMind whose public homepage highlights work on large language models, weak supervision, and knowledge representation.

Research scientist at Ai2 focused on natural language processing, commonsense reasoning, long-form generation, narrative intelligence, and text-based games.

Audio research leader at OpenAI. She previously worked on MuseNet and Jukebox, and earlier studied physics at Princeton and neuroscience at Stanford before a professional career as a classical pianist.

Research Scientist at OpenAI working on deep learning theory, AI alignment, and large language models; he previously completed a PhD at Stanford advised by Percy Liang.

Principal research scientist at NVIDIA working on recursive intelligence, test-time reasoning, AI for biology, multimodal generation, and code generation.

Research scientist at OpenAI focused on multimodal reinforcement learning and natural language processing; PhD candidate at Stanford University.

Distinguished engineer on Google's Gemini LLM team working on machine learning systems, generative AI, and data center infrastructure.

Edward J. Hu is a machine learning researcher known for efficient adaptation methods for large language models, including LoRA and QLoRA. His public profile focuses on parameter-efficient fine-tuning, model editing, and practical LLM systems.

Member of Technical Staff at OpenAI working on large language models. He has also worked on software at YouTube and Google and studied computer science at Stanford University.

OpenAI team member in the San Francisco Bay Area and co-author of the GPT-4 Technical Report.

Member of Technical Staff at OpenAI. Previously at New York University, where he completed a PhD in computer science advised by Kyunghyun Cho. His interests include natural language processing, machine learning, and deep learning.

Senior Staff Software Engineer at Google working on machine intelligence, data management, and large-scale machine learning systems.

Engineer at OpenAI credited in the GPT-4 technical report for reliability engineering. Previously worked on Google App Engine and at LinkedIn, according to his PyCon 2011 speaker profile.

Member of technical staff at OpenAI focused on scientific and technical research on general-purpose AI control, evaluation, and alignment. He previously worked at Google DeepMind and co-founded a startup.

Vice President of Learning and Perception Research at NVIDIA, leading work in computer vision, graphics, and machine learning.

Jason Phang is a machine learning researcher focused on language model robustness, evaluation, and parameter-efficient adaptation. His public profile highlights work on benchmark design, representation learning, and practical LLM methods.

Research scientist and engineer at OpenAI; previously worked at Google DeepMind on language models, reinforcement learning, and robotics, and is known for neural network interpretability and visualization.

Jianmo Ni is a researcher focused on information retrieval, question answering, and large language model systems. His public profile highlights retrieval-augmented generation, ranking, and efficient NLP methods.

Karthik Pattabiraman is a professor of computer science at the University of British Columbia whose research spans software engineering, dependable distributed systems, systems performance, and software security.

Stanford PhD student studying AI evaluation and optimization. Her public profile notes research internships at OpenAI, Anthropic, and Thinking Machines Lab, plus earlier work on human-AI collaboration and reinforcement learning at Princeton.

Kelvin Guu is a researcher working on language models, retrieval, and efficient adaptation. His public profile highlights work on retrieval-augmented generation, in-context learning, and large-scale NLP systems.

Researcher focused on world models, 3D generation, and neural rendering. He is a founding member of World Labs, previously worked at Google on 3D asset generation, and received a PhD from the University of Washington in 2021.

Liam Fedus is a research scientist at OpenAI. OpenAI's staff page says his research interests include reinforcement learning and language models, with a focus on improving capabilities, safety, and robustness.

Lilian Weng is vice president of research at OpenAI. OpenAI's staff page says she works on AI systems that can mimic and reason about our world to improve intelligence.

Member of Technical Staff at OpenAI focused on advancing the capabilities of large language models.

Machine learning researcher and engineer whose public work includes multimodal models, robotics, and reinforcement learning, including research at Cohere.

Peter West is a PhD candidate at the University of Washington studying aligned, grounded, and trustworthy language models. His work focuses on evaluation, human feedback, model behavior, and safer NLP systems.

Research scientist at FAIR Meta working on multimodal learning, image-text retrieval, and language technologies.

Member of technical staff at NVIDIA Research focused on language models, deep learning, and efficient training systems.

Computer science PhD candidate at Stanford working on multimodal learning, reasoning, and human-AI interaction; previously worked with Google DeepMind and Rutgers.

Researcher at DeepSeek and incoming assistant professor at the University of Hong Kong specializing in language, vision, and speech.

Researcher whose public work spans information retrieval, recommendation systems, and large language models.

Sam McCandlish is a research scientist at OpenAI. His public homepage highlights work on scaling laws, optimization, and reinforcement learning, and links to code and publications.

Research scientist at the Allen Institute for AI working on large language models, multilingual NLP, machine reasoning, and model evaluation.

Research scientist at OpenAI.

Co-founder of Dust. Previously worked on general intelligence at OpenAI and on payments and Bitcoin at Stripe.

Taya Hartman is a product and brand designer whose public portfolio spans digital, visual, and interactive work. Public sources tie her to Cohere as a senior designer, and she is credited as a contributor to the Command A technical report.

Thomas Degry is a design engineer at OpenAI based in San Francisco. Public profiles also describe prior work as a design engineer at Stripe and as tech lead for openai.com.

Researcher and engineer focused on robust and aligned AI at Anthropic. He previously worked at OpenAI and Google Brain, and was the lead author of the GPT-3 paper.

Principal scientist at Cohere and adjunct professor at McGill University, with research spanning NLP, machine learning systems, speech, and biometrics.

Research scientist at OpenAI working on reinforcement learning and efficient machine learning; previously completed a PhD at UC Berkeley advised by Sergey Levine.

Research scientist at OpenAI focused on applying AI to medicine and science; previously worked on AI for vision, language, healthcare, and robotics.

Researcher at DeepSeek focusing on pretraining and multimodal models; previously interned at MiniMax and Microsoft Research Asia.

Jian Yang is an Associate Professor at Beihang University whose research focuses on code intelligence, large language models, and AI agents. He worked with Alibaba Qwen from 2023 to July 2025.

Yang Fan is a research scientist at Alibaba Group. His homepage says he works on large language model post-training and deployment.

Research scientist at DeepSeek AI working on multimodal large language models and end-to-end autonomous driving. Earned a PhD in computer science from the Chinese University of Hong Kong.

Yu Wan is a Qwen contributor and co-author listed on the Qwen, Qwen2.5, and Qwen3 technical reports.

Jacob Devlin is a research scientist at Google DeepMind whose work focuses on language models, long-context modeling, and tool use.

Public profiles list Kim Malfacini as head of product policy at OpenAI, with earlier work in public policy and trust and safety for AI systems.

Research scientist focused on foundation models and multimodal large language models; his homepage notes earlier work at DeepSeek AI and current research at the University of Southern California.

Alignment researcher at OpenAI working on making AI understandable to and aligned with human values.

DeepSeek team member and co-author of the DeepSeek-V3, DeepSeek-V2, and DeepSeek LLM technical reports.

Senior research scientist at NVIDIA focused on large language models, reinforcement learning, and inference-time scaling for AI agents. His public NVIDIA author page also notes prior work on robotic grasping, pose estimation, and language understanding.

Research scientist at Meta working on multimodal machine learning and AI. Previously worked on multimodal learning at Google DeepMind and earned a PhD in computer vision and machine learning from Ecole des Ponts ParisTech.

Research scientist at Meta in New York City and research advisor at the UCLA NLP group; previously completed a PhD in computer science at UCLA.

Armand Joulin is a researcher and the cofounder and chief scientist of Mistral AI. Public arXiv records also list him as an author of LLaMA: Open and Efficient Foundation Language Models.

Jason Baldridge is a Research Scientist at Google DeepMind working on natural language understanding, multimodal learning, and evaluation.

Research scientist at Qwen focused on alignment, agentic systems, and multilingual language models; previously worked on post-training at Meta and studied at Renmin University of China.

PhD student at The Hong Kong University of Science and Technology (Guangzhou) whose research interests include large language models, vision-language models, AI agents, and multimodal retrieval.

Liyue Zhang is a research scientist at DeepSeek whose public profiles highlight multimodal models, reasoning, and AI agents.

Research scientist at DeepSeek AI. Previously completed a PhD at Carnegie Mellon University.

Ph.D. student in Computer Science at Zhejiang University and researcher on the Qwen series at Alibaba Group.

CEO of the Allen Institute for AI and professor of computer science at the University of Washington. His work spans computer vision, multimodal learning, reasoning, and embodied AI.

Chief Technology Officer at Google DeepMind, with work spanning machine learning and reinforcement learning.

Researcher at DeepSeek interested in efficient large language models and multimodal large language models.

Research scientist at DeepSeek.

Researcher at Alibaba working on foundation models and agents for enterprise applications.

Member of Technical Staff at Google DeepMind working on machine learning, natural language processing, and large language models.

Assistant professor of computer science at Brown University. Previously completed a PhD in computer science and engineering at UC Santa Cruz.

ML researcher at DeepSeek.

OpenAI co-founder and president whose public work spans the OpenAI API, Codex, Gym, OpenAI Five, and broader large-scale model systems.

Igor Babuschkin is an AI researcher and founder of Babuschkin Ventures. His personal website describes building advanced AI systems; a CNBC profile described him as a former DeepMind research engineer and former OpenAI technical staff member.

VP of Research at Google DeepMind working on robotics and embodied intelligence, with expertise in machine learning, reinforcement learning, neuroscience, and computer vision.

Sam Altman is the CEO of OpenAI.

Mohammad Bavarian is a researcher at OpenAI. His personal site states that he earned a PhD from MIT in 2017 and previously worked as a researcher at Rubrik.

DeepSeek team member and co-author of the DeepSeek-V3, DeepSeek-V2, and DeepSeek LLM technical reports.

OpenAI contributor credited on the GPT-4 Technical Report; previously a Dropbox engineer and a Ph.D. student at UC Berkeley focused on machine learning and robotics.

Saumya Malik is an incoming postdoctoral scholar at Johns Hopkins University and recently completed a PhD in the Machine Learning Department at Carnegie Mellon University. Her interests include interpretability, evaluation, reward learning, and language model agents.

DeepSeek team member and co-author of the DeepSeek-V3, DeepSeek-V2, and DeepSeek LLM technical reports.

Google researcher whose public profile says he joined Google in September 2008 and has been with the Google Brain team since January 2015, with interests spanning information retrieval, learning to rank, machine learning, machine translation, and natural language processing.

Ph.D. candidate at the University of Science and Technology of China whose research focuses on improving the general reasoning abilities of foundational large language models, LLMs for recommendation, and scaling reinforcement reasoning; he lists himself as a core contributor to the Qwen2.5 and Qwen3 technical reports.

Researcher at DeepSeek focused on large language models, reinforcement learning, multimodal large language models, and generative AI.

Research scientist at Ai2 and PhD candidate at the University of Washington. Her work focuses on language models, evaluation, and building practical open-source AI systems.

Senior Research Manager and Senior Director at Tongyi Lab, Alibaba Group, leading agents and AI infrastructure research.

Research scientist at the UK AI Security Institute and former OpenAI member of technical staff who worked on model behavior and post-training research. Previously conducted computational neuroscience research at UC Berkeley.

Research scientist at OpenAI focused on scaling reinforcement learning and self-improving models; previously worked on deep learning for gaming at Nvidia.

Research Scientist at Ai2 focused on natural language processing, reasoning, and grounded commonsense understanding.

Sandeep Subramanian is an Assistant Professor at MBZUAI whose research focuses on grounded language generation, multimodal learning, and large language models.

Research scientist at Alibaba DAMO Academy focusing on aligning and scaling superintelligence.

Research scientist at OpenAI. Previously interned at FAIR and Google Brain and completed PhD research at Carnegie Mellon University.

Member of Technical Staff at OpenAI working on machine learning, reinforcement learning, natural language processing, and large language models.

Research scientist at OpenAI interested in AI safety, alignment, governance, and technical safety.

Computer scientist and AI researcher who co-founded OpenAI and served as its chief scientist.

Member of the Qwen Team at Alibaba Group and a Ph.D. candidate at the Institute of Automation, Chinese Academy of Sciences. His research interests include multimodal reasoning and agents.

Researcher at Qwen, Alibaba Group since 2021, with publications on large language model evaluation and pre-training data management.

Research scientist at DeepSeek AI interested in language models, multimodal large language models, and deep generative models.

Vice president at Google DeepMind in London working on machine learning and reinforcement learning. His public profile notes work spanning policy-gradient methods, distributed and generative models, and robotics.

Machine learning researcher whose public profile highlights work across Berkeley AI Research, RISELab, Sky Computing, and the Ray team.

Research scientist at Meta working on AI agents, language, and reinforcement learning.

Researcher at Alibaba Qwen; formerly a postdoctoral researcher at the University of Cambridge and a PhD in NLP at the University of Edinburgh.

Christopher Clark is a researcher working on language models, efficient inference, and trustworthy NLP systems. His public profile highlights work at the intersection of NLP, efficiency, and model evaluation.

Research director at Google working on music AI, multimodal generation, and human-AI interaction. He co-founded the Magenta project and has led widely used work on music generation with neural networks.

Research scientist at OpenAI working on reinforcement learning and deep learning, with interests spanning language, vision, and sequential decision-making.

Research scientist at OpenAI focused on neural scaling, autonomous learning systems, language models, and reinforcement learning.

Madelaine Boyd is a staff engineer at OpenAI. Her public GitHub profile links to her personal website, and official OpenAI contributions pages list her work on GPT-4 and GPT-4.5.

Researcher at DeepSeek focused on multimodal large language models, world models, reinforcement learning, and embodied AI.

Andrew Cann is a software engineer at OpenAI. His public website and GitHub profile identify him as an OpenAI engineer, and OpenAI's contributions pages list his work on GPT-4 and GPT-4.5.

Benfeng Xu is an LLM post-training researcher at Alibaba Group and an incoming assistant professor at Carnegie Mellon University. His homepage says he works on language models, efficient and trustworthy machine learning, AI for science, and biomedicine.

Applied scientist at Amazon focused on natural language and speech processing, machine learning, and multimodal learning.

Chengyuan Li is a research intern with Alibaba's Qwen team. His homepage highlights work on reasoning and post-training for large language models.

Research scientist at Cohere working on large language models and machine reasoning; previously worked on deep learning at Google Brain and Google DeepMind.

Research scientist at OpenAI interested in general intelligence; previously studied computer science and cognitive science at Stanford and UC Berkeley.

Senior applied scientist at Amazon working on large language models, multimodal AI, and efficient deep learning.

PhD student at Tsinghua University researching multimodal large language models, digital avatars, and 2D/3D content generation; previously an AGI student researcher at DeepSeek AI who led DreamCraft3D and contributed to DeepSeek-VL.

Research scientist at OpenAI working on core post-training and previously on pre-training, with interests in personalized and safe AI.

Technical staff at OpenAI interested in the theoretical foundations and algorithms for large language models and reinforcement learning.

Empirical AI researcher at the Allen Institute for AI whose work focuses on post-training, synthetic data, and evaluation.

Senior staff research scientist at Google DeepMind whose work spans large language model post-training and pretraining data.

Thomas Lavril is a research scientist at Mistral AI based in Paris, formerly at Google DeepMind. His personal site highlights work on foundation models, multimodal learning, representation learning, and machine learning for biology.

Research scientist at OpenAI working on pretraining and reasoning; previously studied computer science at Stanford University.

Member of Technical Staff at OpenAI focused on safety evaluations, economic impact evaluations, and democratic inputs to AI.

Associate Professor in the Department of Computer Science at the University of Alabama at Birmingham whose research spans computer security, machine learning, pattern recognition, biometrics, and formal methods.

Research scientist at DeepSeek AI focused on multimodal large language models, reinforcement learning, and efficient post-training.

Yunxing Dai is a researcher at OpenAI and a co-author of the GPT-4 Technical Report. His public homepage and Google Scholar profile provide verified research identity links.

Researcher in natural language processing and pre-trained language models, with public academic work from Tsinghua University and related NLP publications.

Researcher at Cohere working on machine learning, natural language processing, and computer vision.

Researcher at OpenAI working on multi-agent systems; previously at Google DeepMind and the University of Michigan.

Carlos Riquelme is a Senior Research Scientist at Google Research in New York City. His public work uses reinforcement learning and meta-learning to improve large language models.

Devendra Singh Chaplot is a research scientist at Mistral AI working on language models and multimodal AI.

Researcher at OpenAI; previously worked at NVIDIA, IBM, and GetNinjas, with prior research at the Neuroinformatics Lab.

Research scientist at OpenAI with a background in theoretical physics, computational neuroscience, and theoretical AI.

Developer at OpenAI focused on agents; angel investor and advisor; previously led developer relations roles at Google and Apple.

Xuezhi Wang is a Research Scientist at Google DeepMind whose public work focuses on reasoning and systematic generalization in language models, along with robustness and fairness in natural language processing. She received her PhD from Carnegie Mellon University in 2016.

Professor at Stanford University and senior director at the Allen Institute for AI. Her research spans natural language processing, commonsense reasoning, and multimodal AI.

Research scientist at Alibaba Qwen working on LLM post-training, RLHF, reasoning, and evaluation; incoming assistant professor at Renmin University of China.

Member of Technical Staff at DeepSeek focusing on large language models and reinforcement learning.

Research scientist at Meta working on post-training and model personalization. He previously worked on retrieval systems, recommendations, and ranking, and earned his Ph.D. from Stanford University.

Staff research scientist at Meta whose work focuses on democratizing natural language processing tools, especially for low-resource languages.

Member of the Cybersecurity Policy and Insights team at OpenAI covering the intersection of technology, international security, and geopolitical competition.

Member of the Llama team at Meta working on post-training, evaluation, and model reliability. He previously worked at AI2 and completed a Ph.D. in computer science at Stanford.

Senior research scientist at AWS AI Labs and professor at the University of Edinburgh whose work spans machine translation and multilingual language technologies.

AI researcher at OpenAI working on reinforcement learning and reasoning.

Researcher at Moonshot AI focused on reinforcement learning and robotics. He earned a Ph.D. in robotics and machine learning from Carnegie Mellon University.

Senior researcher at Microsoft Research and lecturer at Northeastern University. Public profile notes prior work at OpenAI.

OpenAI contributor with a personal homepage and GitHub profile covering NLP and language model research.

Research scientist at Anthropic focused on AI safety and alignment; previously Head of Alignment and co-led the Superalignment team at OpenAI.

Researcher at Alibaba DAMO Academy with a background in natural language processing, speech, and recommender systems.

Principal researcher at Tongyi Lab, Alibaba Group, and member of the Qwen team focusing on multimodal large models.

Member of technical staff at OpenAI whose public profile notes a PhD in computational neuroscience from Princeton University.

Researcher at OpenAI focused on improving the efficiency and reliability of AI systems.

Researcher whose public profiles include Amazon Science and USC ISI; his work spans dialogue systems, temporal reasoning, and document retrieval.

Peter J. Liu is a co-founder of Twenty Labs. Previously he was a research scientist at Google DeepMind, where his public work focused on language modeling from pre-training through fine-tuning and post-training, after earlier production machine learning work on Gmail Spam.

OpenAI contributor with a personal homepage and GitHub profile covering software and AI engineering projects.

Researcher and writer focused on safe and beneficial AI; listed as a contributor to GPT-4 by OpenAI.

Senior research scientist at Ai2 and project lead of OLMoE, working on language models, reasoning, and alignment.

Machine learning researcher and research leader whose work spans deep learning, representation learning, and neural language modeling; his public profile lists him as an Apple Distinguished Scientist in AI/ML.

Research scientist at DeepSeek AI interested in scaling laws, large language models, and reinforcement learning.

Research scientist at Google working on multilingual generation, machine translation, and large language model systems. His public work spans translation quality, evaluation, and scalable language technology.

Applied scientist at Cohere focused on natural language processing and machine learning.

Researcher with public work on large language models. Official Qwen materials credit her on Qwen releases, and public profiles include DBLP and OpenReview.

Member of technical staff at OpenAI. Previously pursued a PhD at Stanford University, focusing on practical reinforcement learning and bandits.

Engineer at OpenAI working on the API; previously built products and customer experience systems at Stripe and Instacart.

Vishal Kuo is a member of technical staff at OpenAI.

Co-founder and research lead at OpenAI. Public profile notes prior study in computer science and mathematics at New York University.

Member of technical staff at xAI; previously a research scientist at DeepSeek AI and a PhD student in Computer Science and Engineering at the University of Michigan.

Ph.D. candidate in computer science at Princeton University working on LLM agents and machine learning. He is a coauthor of Moonshot AI's Kimi k1.5 report.

Researcher with public work on large language models. Official Qwen materials credit him on Qwen releases, and public profiles include DBLP and OpenReview.

Tsinghua University PhD student whose public OpenReview profile lists a 2024 DeepSeek-AI research internship and interests in scalable foundation models, multi-agent systems, and controllable AIGC.

Machine learning engineer at Apple Intelligence; previously a researcher at DeepSeek and a PhD student in computer science at Michigan State University.

Daniel Mossing is a research scientist at OpenAI. His OpenReview profile also lists past affiliations with UC Berkeley and New York University.

Alibaba senior technology leader and researcher associated with Qwen. Public profiles list him with Alibaba Group, and official Alibaba Cloud coverage identifies him as a chief technology officer leading large-model work.

Staff research scientist at Google DeepMind interested in deep learning theory and applications, with a focus on scaling and reinforcement learning.

OpenAI team member and co-author of the GPT-4 Technical Report.

Senior applied research scientist at NVIDIA focused on pretraining and post-training methods for large language models, multimodal learning, and synthetic data generation.

Carolyn Zhang is a researcher focused on large language models, natural language processing, and machine learning.

Research scientist at Google DeepMind.

Research scientist and engineer working on large-scale machine learning. His personal site highlights contributions to GPT-3, GitHub Copilot, and Stable Diffusion.

Clément Gehring is a research scientist at Mistral AI working on efficient, multilingual, and general-purpose language models. He is also known for influential early work on neural machine translation, including convolutional sequence-to-sequence models.

Member of technical staff at Cohere Labs, where he works on models for code, reasoning, and agents and contributes to post-training.

Dragomir Radev is an Eminent Professor of natural language processing at MBZUAI. His research spans NLP, information retrieval, question answering, and summarization, and he is also a coauthor of the Nemotron-4 15B technical report.

Member of technical staff at OpenAI interested in empirical machine learning and exploration in reinforcement learning; previously a PhD candidate at MIT.

Senior research scientist at NVIDIA focused on large language models and reasoning systems. His public NVIDIA author page notes more than eight years of machine learning work spanning NLP, forecasting, recommender systems, and computer vision.

Senior research scientist at NVIDIA working on multimodal and embodied AI, including multilingual multimodal large language models and human-centered robot learning.

Laura Buesing is a research scientist at Google DeepMind working on machine learning and computational neuroscience, with a focus on agents that remember, reason, and plan.

Manaal Faruqui is an NLP and large language model researcher whose public profile covers factuality, instruction following, conversational systems, and language understanding. His work spans large language model post-training as well as earlier research on word representations, question quality, and dialogue systems.

Mary Phuong is an AI researcher focused on making large-scale AI systems more trustworthy, effective, and aligned with human values. Her public profile spans work at DeepMind and Cohere, and she is currently a fellow at Stanford HAI studying foundation-model governance and societal impacts.

Moein Khazraee is a postdoctoral researcher at LMU Munich and a visitor at Google DeepMind. His research focuses on reliable and trustworthy machine learning for language, knowledge, and reasoning.

Senior research scientist at NVIDIA focused on embodied agent AI, simulation and rendering, computer vision, robot learning, and AI in science.

Nima Rajani is a research scientist at Ai2 whose work focuses on trustworthy, interpretable, and verifiable AI systems.

Research scientist at OpenAI focused on generative models and unsupervised learning. He studied computers, mathematics, and physics at MIT and has contributed to models including GPT-3, Jukebox, and DALL·E.

Researcher and engineer whose public homepage lists work on multimodal reasoning, robustness, and mechanistic interpretability; he was an OpenAI Resident and is credited on the GPT-4 technical report.

Inventor, author, and futurist serving as Principal Researcher and AI Visionary at Google, known for long-running work on AI, language technology, and human-computer systems.

Sarath Chandar is an associate professor at Polytechnique Montreal, a core academic member of Mila, and a CIFAR AI Chair. His research focuses on continual learning, reasoning, meta-learning, reinforcement learning, and recurrent neural networks.

Principal researcher and research manager at Microsoft Research AI Frontiers in Cambridge, UK.

Siddharth Narayan is a researcher focused on natural language processing and AI, with applications that include healthcare.

Applied research scientist at NVIDIA working on reinforcement learning for large language models, post-training, and data curation.

Thomas Scialom is a research scientist at Ai2. His work focuses on reasoning, data quality, and post-training for language models.

OpenAI team member and co-author of the GPT-4 Technical Report.

Research scientist at Amazon AGI and assistant professor at Yale School of Medicine whose work focuses on diffusion models, equivariant deep learning, and generative models for molecules and proteins.

DeepSeek team member and co-author of the DeepSeek-V3 Technical Report.

Distinguished software engineer at Google Brain focused on large-scale computer systems and machine learning applications.

Researcher on Alibaba's Qwen team focused on large language models and NLP, with public research profiles listing a Nankai University background.

Generative AI Research Scientist at Meta and founder of Baobab AI Labs, with work spanning multilingual models, open-source LLMs, machine translation, and story generation.

AI researcher whose public work includes large language models, vision-language models, and multimodal systems. His public profile notes prior work as a senior algorithm expert at Alibaba and co-authorship of Qwen technical reports.

Timothee Lacroix is a machine learning researcher whose public work includes multilingual representation learning and open language models.

Yu Wu is a researcher at DeepSeek AI and head of its LLM Alignment Team. His public homepage highlights work on reinforcement learning and alignment for the DeepSeek model family, including DeepSeek-V3, DeepSeek-R1, and DeepSeekMath, and notes prior work at Microsoft Research Asia.

Research scientist at DeepSeek interested in large language models, reinforcement learning, robot learning, and machine learning.

Alibaba researcher working on large language models and multimodal pretraining; public research profiles connect An Yang to Qwen-related work and earlier study at Peking University.

Researcher at Alibaba Group working on natural language processing and multimodal AI.

Researcher at DeepSeek and former master's student in EECS at Peking University. Public profiles list work on LLMs, multimodal systems, transformers, BERT, and machine translation.

Ivo Danihelka is a research scientist at Google DeepMind whose public profile highlights deep learning research and machine learning publications.

Tara N. Sainath is a distinguished research scientist and director at Google DeepMind whose work focuses on speech recognition, spoken language understanding, and multimodal large language models.

Researcher and engineer at Mistral AI focused on distributed machine learning and efficient large language models.

Research scientist at DeepSeek.

Engineer at OpenAI working on inference infrastructure, product engineering, and prototyping for systems including GPT-4 and DALL-E 2.

Research scientist at Mistral AI working on machine reasoning and probabilistic deep learning.

Vice President of AI Research at NVIDIA leading generative AI and conversational AI research; previously led Amazon Alexa AI and held faculty roles at the University of Illinois Urbana-Champaign and Bilkent University.

Edouard Grave is a machine learning researcher whose public work spans representation learning, natural language processing, and large language models.

Research scientist working on large language models and retrieval-augmented generation; creator of the open-source project tiny-universe.

Research scientist at the Allen Institute for AI (Ai2) whose work focuses on natural language understanding and commonsense reasoning.

Researcher on Alibaba's Qwen team focused on pre-training and post-training for multimodal large language models and reasoning.

DeepSeek team member focused on pretraining, post-training, and efficient scaling for large language models.

Rogerio Feris is a principal research scientist and manager at the MIT-IBM Watson AI Lab. His work focuses on multimodal AI, efficient representation learning, and large language models with long-term memory.

Research scientist at Qwen focused on dialogue systems, large language models, reinforcement learning, game theory, and decision-making.

Research scientist in Tongyi Lab whose official profile highlights post-training and multimodal large language models.

Research scientist at DeepSeek AI. His homepage also describes him as a PhD candidate in computer sciences at the University of Wisconsin-Madison.

Research scientist at Google DeepMind on the Gemini team, working on multimodal AI.

Engineer and founder who previously worked at OpenAI, Palantir, and Lyft and now builds the AI search startup Basalt. He publishes public writing on AI products and software on his personal site.

Research scientist at DeepSeek working on post-training and reinforcement learning, with interests in systems and AI for science.

Aäron van den Oord is a Google DeepMind researcher known for generative and sequence-model research.

Researcher at OpenAI and co-creator of DALL-E who works on multimodal generative models and image generation.

Aidan Gomez is the CEO and co-founder of Cohere and a coauthor of the Transformer paper Attention Is All You Need.

Research scientist at Google DeepMind working on multimodal and generative AI for healthcare.

Chris Bamford is a researcher at Mistral AI working on foundation models and multimodal systems.

Eric Hambro is a machine learning researcher and entrepreneur whose prior work includes contributions at Meta AI and the LLaMA project.

Member of technical staff at OpenAI whose public profile notes leadership of the MT+MX team from 2020 to 2025 after earlier engineering work at Google.

Staff scientist at Tongyi Lab, Alibaba Group, and Qwen team member working on multimodal language models, AI agents, evaluation, reasoning, and information extraction.

Research scientist known for language modeling and multimodal systems; OpenAI credited him as a deployment research and evals lead and architecture contributor on GPT-4V.

Jianfeng Gao is a researcher in natural language processing and multimodal foundation models whose public homepage and Google Scholar profile highlight work on dialogue systems, retrieval, reasoning, and vision-language models.

Research scientist at OpenAI working on reinforcement learning and robotics, with a PhD from UC Berkeley.

Senior research scientist at NVIDIA focused on language and vision models and applied multimodal AI.

Julian Schrittwieser is a Google DeepMind researcher known for reinforcement learning and game-playing systems.

Keming Lu is a research scientist at Tongyi Lab, Alibaba Group in Beijing and a co-author of the Qwen and Qwen2.5 technical reports.

Z.ai researcher focused on multimodal large language models and computer vision, with interests in large-model training and post-training.

Research scientist at Google DeepMind based in Paris, focused on deep learning and computer vision.

DeepSeek team member focused on scaling large language models, multimodal models, and large-scale reinforcement learning.

Developer and researcher with public GitHub activity on DeepSeek-AI repositories including DeepSeek-VL2, plus coauthor credit on the DeepSeek-V2 and DeepSeek-V3 technical reports.

Assistant Professor at the University of Washington whose research focuses on machine learning, AI safety, and evaluation; he is a co-lead of the OLMo language model project.

Researcher and engineer working on language models and reinforcement learning, with public work spanning Alpaca, emerging agents, and large-model evaluation.

Research scientist at Ai2 specializing in open language models, reasoning, and multi-agent systems.

DeepSeek researcher. Public OpenReview and Hugging Face profiles identify Z.Z. Ren with DeepSeek and list work on theorem proving and synthetic training data for reasoning models.

Member of technical staff at OpenAI working on post-training. Previously worked on climate and sustainability software and on policy and product efforts related to the electric transition.

Yu Liu is publicly listed as a co-author on the 2025 Seed1.5-VL, MiniMax-01, and MiniMax-M1 technical reports.

Akhil Mathur is a postdoctoral research scientist at Meta FAIR whose public homepage highlights work in natural language processing and machine learning.

Alan Schelten is a research engineer at Meta working on large language models, reinforcement learning, and deep learning. His public homepage also lists prior research experience at Berkeley, OpenAI, and BAIR.

Engineer at OpenAI. Formerly worked on generative AI at Disney and on data science projects with organizations including MIT and Tufts, and studied at MIT.

Research scientist at Meta AI working on applied mathematics, machine learning, and artificial intelligence.

Research scientist at FAIR Meta and teacher affiliated with ENS, INRIA, and PSL.

Cameron Raymond is a software engineer at OpenAI. His personal site says he previously worked at Asana, led developer experience at Stripe, and is an author of Staff Engineer.

Research manager at OpenAI with a public site covering publications and projects.

David Karamcheti is a research scientist at Google DeepMind whose public homepage highlights work on multimodal foundation models and embodied intelligence.

Researcher at OpenAI working on multimodal and agentic systems. He previously worked on machine learning systems and video understanding, and is completing a PhD at Columbia University.

David Wadden is an assistant professor at the University of Washington working on natural language processing and AI systems for science and high-stakes domains. His public profile highlights information extraction, scientific NLP, and trustworthy language model applications.

Research scientist at Google DeepMind working on language models, multimodal learning, evaluation, and alignment.

Software engineer at Meta building intelligence for wearables; he previously worked on developer infrastructure for language models and assistant products, as well as on-device NLP systems.

PhD student in Computer Science at Stanford University and affiliated with OpenAI. Her research focuses on natural language processing and machine learning, and she is a co-author of the GPT-4 Technical Report.

Research scientist at Mistral AI and PhD candidate at Mila whose interests include causal representation learning, world models, and reinforcement learning.

Engineer and product builder who has worked on ChatGPT, Codex, the OpenAI API, and developer tools. He publishes writing and code on his personal site and GitHub.

Research engineer at Alibaba Tongyi Lab focusing on pre-training, post-training, and efficient architecture for large language models.

Researcher at OpenAI focused on large language models and embodied AI. Her public background includes AI and recommendation work at TikTok, computer vision and robotics research at Stanford, and an ML master's at Princeton.

Research scientist working on multimodal language agents and reinforcement learning. He has worked at OpenAI and Meta FAIR, and earned a PhD from Stanford.

Shusheng Yang is a research scientist in Tongyi Lab at Alibaba Group. His work focuses on natural language processing and machine learning, especially pre-trained language models, text generation, and efficient NLP.

Researcher working on large language model interpretability at Anthropic. He previously worked on scaling laws at OpenAI, earlier did ML engineering at Beehive AI, and completed a PhD in physics at Stanford.

Tomi Pott is a research engineer at Meta Research whose public homepage highlights work in multi-agent reinforcement learning, deep learning, and AI systems.

Researcher in multimodal large language models at the Alibaba Qwen team and student at Johns Hopkins University.

Senior member of technical staff at OpenAI focused on machine learning systems and AGI. He previously co-founded DeepGPU and publishes public writing and code on his website and GitHub.

Research intern at DeepSeek and a Tsinghua University undergraduate focused on machine learning systems and large language model inference.

Zizheng Pan is a researcher at DeepSeek working on large language models and reinforcement learning. He previously worked on autonomous driving at Momenta and Megvii and interned at Amazon and Tencent.

Assistant professor at Carnegie Mellon University and scientist at Ai2, working on natural language processing and machine learning with a focus on grounding, multilinguality, and robustness.

Machine learning engineer at FAIR at Meta AI and incoming PhD student at Carnegie Mellon University.

Abhishek Rao is a Research Scientist at Google DeepMind working on machine learning and natural language processing, with interests including structured prediction, reasoning, compositionality, and controllable generation. He has contributed to large language model research including PaLM.

Research scientist at the Allen Institute for AI and PhD candidate in computer science at the University of Washington. Her public profiles focus on language agents, reasoning, and retrieval-augmented language models.

Andras Sarkozy is a senior staff research scientist at Google DeepMind in London. His public profiles describe work on machine learning and natural language processing, with interests in code generation and reasoning in language models.

AI safety researcher whose public work includes OpenAI model policy research and later alignment work at Anthropic, with contributions credited on OpenAI GPT-4o-era projects.

Research scientist at NVIDIA working on large language model post-training and inference.

OpenAI contributor with a personal website covering research and writing.

Research scientist at NVIDIA focused on post-training and scalable evaluation for language models; previously worked on conversational AI at Amazon Alexa and on user-facing machine learning at Apple.

Ariel Herbert-Voss is a computer scientist whose public homepage notes previous work on AI safety and special projects at OpenAI, along with later work on digital humans and universal basic income initiatives.

Research engineer at OpenAI focused on reinforcement learning and human-computer interaction; previously co-founded the local-first AI startup Ted AI.

Program manager at OpenAI working across finance, legal, operations, and communications, after earlier work in philanthropy, marketing, and project management.

Member of technical staff at OpenAI, author of Dive into Deep Learning, and a core contributor to the Llama 3 model. He earned his Ph.D. in computer science from the University of Illinois Urbana-Champaign.

Public profiles list Bianca Martin as chief of staff at OpenAI, with an Oxford background in philosophy, politics, and economics.

Research scientist at NVIDIA with publications in machine learning and embodied AI.

Researcher with public work on large language models. Official Qwen materials credit him on Qwen releases, and public profiles include DBLP and OpenReview.

Researcher and engineer with public work on similarity search and large model systems. Public profiles list Zhejiang University, and DeepSeek open-source releases credit him on projects including DeepSeek-VL and DualPipe.

Research Scientist at OpenAI with public work in machine learning and generative models.

Research scientist at Google DeepMind whose work focuses on machine learning, speech, and large language models.

AI law and policy researcher and Director of Research at the Institute for Law & AI; previously held policy and legal roles at OpenAI.

Google researcher working on machine learning, computer vision, and natural language, and a co-author of the PaLM 2 technical report.

AI2 researcher working on multimodal language models, evaluations, instruction tuning, and preference alignment, and a co-author of Open Instruct.

AI researcher focused on epistemic safety for advanced AI systems, including uncertainty and out-of-distribution detection.

Daniel Khashabi is an assistant professor of computer science at Johns Hopkins University. His research focuses on trustworthy language-driven AI, natural language processing, reasoning, and human-AI interaction. Previously, he was a postdoctoral fellow at the Allen Institute for AI.

Researcher at Cohere working on large language models. Her public homepage highlights interests in privacy-preserving machine learning, robust machine learning, natural language processing, and reinforcement learning.

Engineer at OpenAI who spoke publicly about fine-tuning GPT-4 at DevDay.

Research scientist at Google working on machine learning and language models. His public work includes efficient model architectures, language understanding, and large-scale training.

Research scientist and engineer working on machine learning and distributed systems, with large-scale language model contributions including PaLM 2.

Vice President of Research at Google DeepMind. His work spans search, recommendation systems, human-computer interaction, and practical applications of large language models.

Lead researcher at OpenAI whose official profile focuses on speech and audio.

Eric Hu is a designer and creative director whose public portfolio spans technology, fashion, music, and architecture. At Cohere he served as VP of Design and is credited as a contributor to the Command A technical report; his public work also includes earlier design leadership roles at Nike and SSENSE.

Research scientist at Google DeepMind working on language models and efficient sampling and serving.

Research scientist at Meta working on large language models, large-scale reinforcement learning from human feedback, retrieval, recommendation systems, and machine learning systems.

AI researcher at Meta with public work on foundation models, optimization, and machine learning evaluation.

Research scientist at NVIDIA working on language and vision models.

Allen Institute for AI researcher working on NLP, machine learning, and AI, and a co-author of Open Instruct.

Chief Communications Officer at OpenAI; previously held communications leadership roles at Apple and worked earlier in journalism.

PhD student at KAUST and predoctoral researcher at DeepSeek focused on reasoning, alignment, post-training, and multimodal large language models.

Research scientist at OpenAI working on multimodal understanding, reasoning, and agents; formerly a Ph.D. student at Seoul National University.

Research engineer at OpenAI and contributor to GPT-4.

Technical staff member at Anthropic working on alignment and large language model robustness, previously a research scientist at Google DeepMind and credited on the GPT-4 technical report.

Research scientist at OpenAI working on reinforcement learning and AI alignment. Previously a PhD student in computer science at Harvard University.

OpenAI contributor with a public GitHub profile covering engineering projects.

Researcher at Anthropic focused on scalable oversight and AI safety. He previously worked at OpenAI on language models, led the GPT-3 paper, and earlier studied physics and machine learning.

Research scientist at Amazon AGI.

Professor emeritus of computer science at Jean Monnet University whose work includes natural language processing and large language model adaptation and evaluation.

Researcher in natural language processing, low-resource languages, machine translation, and responsible AI; publicly listed as a PhD candidate at UC Santa Barbara and a co-author of Tulu 2.

Works at OpenAI on reasoning and general intelligence, and co-authored the GPT-4 Technical Report.

Member of technical staff at OpenAI whose official profile highlights multimodal models and intelligence.

Julian Martin Eisenschlos is a Research Scientist at Ai2. His work focuses on natural language processing, language models, and instruction tuning, including contributions to the Tulu 2 project.

Research scientist at Google DeepMind working on data compression, efficient language models, and multilingual modeling.

Research scientist at Amazon AGI and former Stanford University PhD student.

Staff research scientist at Meta whose work focuses on multilingual and multimodal AI, reasoning, and safety.

Research scientist at Google DeepMind working on natural language understanding and machine learning.

Research scientist at Google DeepMind working on machine learning and natural language processing.

Associate professor at ShanghaiTech University working on natural language processing and machine learning.

Professor of Electrical and Computer Engineering at KAUST whose research focuses on machine learning and AI, including edge intelligence, tinyML, efficient AI, and uncertainty-aware learning.

Program manager at OpenAI leading contracting, revenue, pricing, and finance operations, after earlier operations and finance roles at Tesla and Capchase.

OpenAI contributor with a personal website and public engineering projects.

Qwen team member with an official public profile on qwen.ai.

Research scientist at Google DeepMind whose work focuses on pre-training, post-training, and reasoning for large language models.

Research scientist at NVIDIA Research working on computer vision, machine learning, and deep learning, and a co-author of the Nemotron-4 340B technical report.

Co-founder of DeepSeek who leads pre-training and post-training research, with a focus on language models, reasoning models, and reinforcement learning.

Research scientist at Mistral AI with a public publication record on Google Scholar and DBLP.

Research scientist at Google DeepMind focused on multimodal and embodied AI. His work covers computer vision, video understanding, and machine learning for interactive systems.

OpenAI contributor to GPT-4 evaluation and analysis, including Evals open-sourcing, instruction-following evaluation, and API model evaluations.

Senior staff research scientist at Google DeepMind and assistant professor at the Czech Technical University in Prague.

Senior applied scientist at NVIDIA focusing on generative and agentic AI, language models, information extraction, multimodality, and reasoning.

Merry Mou is a researcher at Ai2 whose public homepage and Google Scholar profile highlight work on language model post-training, evaluation, and open-source foundation models.

Harvard computer scientist and professor whose research spans algorithms, probability, information theory, and data streams.

Researcher at Microsoft.

Senior research fellow at the Institute for AI Policy and Strategy and former OpenAI research scientist focused on AI governance and policy.

Distinguished scientist at Amazon AGI in San Francisco; previously at Google Brain and co-founder of Adept AI Labs, with research in natural language processing and machine learning.

Founder and CEO of Thinking Machines Lab and former CTO of OpenAI.

Member of technical staff at OpenAI focused on multimodal post-training and audio reasoning. Previously, she worked on Gemini post-training at Google DeepMind.

Research scientist at Google DeepMind working on natural language processing, speech, and multimodal machine learning.

Research scientist at Apple Foundation Models working on large language models and multimodal systems; previously a research scientist at Google and Meta.

Researcher at OpenAI working across multimodal systems, reasoning, and new product experiences, with earlier roles at Google and YouTube.

Communications and marketing leader at OpenAI working on Sora; previously led the Artist Access Program and earlier worked at Apple, WIRED, and USA TODAY.

Nawshad Farruque is a designer based in Toronto whose public work spans digital product and visual design. Public sources tie him to Cohere as a staff designer, and he is credited as a contributor to the Command A technical report.

Head of product for ChatGPT at OpenAI. He works on ChatGPT and related product experiences, including agent-style workflows and consumer AI tools.

Research scientist at OpenAI.

Machine learning researcher at Cohere whose work focuses on large language models and post-training.

Research scientist at Cohere whose work focuses on deep learning and large language models.

Applied AI researcher at OpenAI working on productivity, software engineering, and agents, with prior product leadership experience across identity, trust and safety, and commerce.

Research scientist at Google DeepMind focused on learning with reward feedback and reasoning in large language models.

Research scientist working on large language models, scaling, alignment, and language; public work includes machine translation robustness, data selection, CodeGemma, and reward overoptimization in LLMs.

Pavan Balaji is a computer scientist and research leader in high-performance computing. His public profiles include work at NVIDIA and leadership of the Argonne Leadership Computing Facility, with research spanning parallel programming models, communication libraries, and runtime systems.

Research scientist at Google DeepMind focused on natural language processing and code generation; previously a part-time research collaborator at Facebook AI Research.

Pratyusha Kamesetty is a deep learning research scientist at NVIDIA and a PhD candidate in computer science at Stanford University. Her research focuses on language models, recommendation systems, and generative AI for music and video.

Preston Tuggle is a distributed systems engineer at OpenAI.

Research scientist at NVIDIA.

Technical staff member at OpenAI. Previously completed a PhD at Stanford University and was a research fellow at the Simons Institute for the Theory of Computing.

Rishiraj Adhikary is a senior applied research scientist at NVIDIA working on AI systems and generative AI.

Research scientist at NVIDIA.

DPhil candidate in Engineering Science at the University of Oxford whose work spans cybersecurity, machine learning, and natural language semantics.

Research scientist at Meta working on language models and machine translation.

Researcher at DeepSeek focused on multimodal models, AI agents, and efficient large language models; previously worked on large-scale recommender systems at Tencent and Kuaishou.

Research scientist at Cohere working on multimodal and embodied AI, robotics, and machine learning systems.

Research scientist at Cohere whose homepage highlights work on efficient and reliable natural language processing, following earlier research engineering work at Google.

Assistant professor at the University of California, Berkeley and research scientist at the Allen Institute for AI. Her public homepage highlights work on language models, natural language processing, pretraining, post-training, and test-time computation.

Principal applied scientist at NVIDIA whose public work focuses on applied machine learning and large language models.

Machine learning researcher focused on reliable ML systems. She was a postdoc in Computer Science at Stanford and earned her PhD from MIT.

OpenAI contributor with an official OpenAI profile page; public contribution pages list work on GPT-4, GPT-4o, and DALL-E 2.

Research scientist at Cohere whose work focuses on natural language processing and language models.

Research engineer at Meta working on Llama models and generative AI. She previously completed an MS in computer science at New York University.

Research scientist at the Allen Institute for AI focused on training, evaluating, and interpreting language models, with work spanning NLP and computational social science.

OpenAI member building agentic products; previously founded the AI note-taking app Circleback and writes about AI, product, and startups.

Sina Samangooei is a machine learning researcher whose public work includes multimodal learning and open language models.

Machine learning researcher at NVIDIA focused on large language models and reinforcement learning.

Engineer and builder who co-founded comma.ai and previously led self-driving at OpenAI, with public work spanning autonomous driving, AGI, and music.

Assistant professor at Cornell Tech whose research focuses on human-AI interaction, AI copilots, and tools that help people learn, create, and make decisions with AI.

Mathematician and machine learning researcher whose NYU profile describes him as a PhD student in mathematics, advising at NYU Shanghai and a research intern at Google DeepMind; he also co-authored AlphaGeometry and the Gemma report.

Research scientist at Ai2 working on personalized language models, instruction tuning, and reinforcement learning from human feedback.

Researcher at Cohere.

Venkatesh Akella is a professor of electrical and computer engineering at the University of California, Davis and director of the Center for AI and Experimental Futures. His research includes machine learning, trustworthy AI, causal AI, computer vision, robotics, and intelligent systems.

Research scientist at Ai2 and PhD student at UC Berkeley working on language models, multilingual NLP, and evaluation.

Senior research scientist at Alibaba focused on large language models and agent learning.

Research scientist at Google DeepMind and incoming assistant professor at Stanford GSB working on AI and economics.

Developer and researcher with public GitHub activity on DeepSeek-AI repositories including DeepSeek-R1 and DeepSeek-VL2, plus coauthor credit on the DeepSeek LLM Technical Report.

Xipeng Qiu is a Fudan University professor whose public work focuses on natural language processing and large language models.

Yusuke Iwasawa is an Assistant Professor in Computer Science at the University of Tokyo whose work spans human-computer interaction and machine learning.

Research scientist at DeepSeek and a Ph.D. student in the School of Software at Tsinghua University. His research interests include large language models and multimodal learning.

Tony Gracious completed his PhD in the Department of Computer Science and Automation at IISc Bangalore. His work includes representation learning, temporal point processes, and higher-order interaction forecasting, and he later joined Dolby's Advanced Technology Group in Bangalore.

Chief AI scientist at Mistral AI and co-founder of Kyutai. Previously worked on large language models and machine translation at Meta and earned a PhD in computer science at Sorbonne University and Inria Paris.

Member of Technical Staff at DeepSeek.

Vice President of Applied Deep Learning Research at NVIDIA, leading work on conversational AI, generative AI, and accelerated deep learning software.

Research scientist at DeepSeek with public GitHub work on language models and AI systems.

Research scientist at DeepSeek with public GitHub projects on AI systems.

CEO and co-founder of Anthropic. Before Anthropic, he served as vice president of research at OpenAI.

Jie Zhou is a Moonshot AI contributor and co-author of Kimi k1.5: Scaling Reinforcement Learning with LLMs.

Researcher affiliated with the Qwen team at Alibaba Group on Google Scholar and coauthor of the Qwen and Qwen3 technical reports.

Research scientist in Tongyi Lab whose official profile highlights work on efficient reinforcement learning, generalization, inference-time scaling, and reasoning for large language models.

Research scientist at Mistral AI working on generative AI. Previously worked as a research scientist at Meta AI, with broader interests spanning machine learning, computer vision, and cryptography.

Research scientist at Google DeepMind working on language model reasoning and AI safety. He previously worked as a member of technical staff at Anthropic.

Research scientist at Google DeepMind focused on long-context and memory-augmented models. His public profile describes work on architectures and algorithms that help models reason over real-world data.

Researcher at OpenAI working on reasoning and scalable oversight, with prior work on chain-of-thought prompting, instruction tuning, and aligning language models with human preferences.

Researcher at OpenAI working on language model training and evaluation, and co-author of the GPT-4 Technical Report.

Professor at the University of Washington whose public research spans NLP, machine learning, and semantic parsing; arXiv author results include OLMo and OLMo 2.

Machine learning scientist at Ai2 working on reinforcement learning, language models, and online social systems.

Research scientist at Qwen, Alibaba, whose public OpenReview profile lists work on vision-language models and large language models.

Research scientist at Z.ai focused on multimodal understanding and generation, large language models, and reinforcement learning. He works on pre-training, post-training, and evaluation of multimodal models.

Research scientist at Z.ai focused on multimodal understanding and generation, reinforcement learning, AI agents, and end-to-end models. He received a bachelor's degree from Tsinghua University and a master's degree from UCLA.

Lead of OLMo, AI2's open-source frontier language models, and Associate Director of the OLMo team at the Allen Institute for AI.

Soumya Batra is a PhD student in computer science at Stanford University and a former research intern at FAIR and Facebook AI Research.

Research engineer at DeepSeek-AI and co-author of the Nature paper introducing DeepSeek-R1.

DeepSeek team member and co-author of the DeepSeek-V3, DeepSeek-V2, and DeepSeek LLM technical reports.

Jin Chen is publicly credited as a co-author on the DeepSeek-V2, DeepSeek-V3, and Seed1.5-Thinking technical reports. Public evidence in this pass supports report authorship, but not stronger biographical or employment detail.

Researcher credited as a co-author on DeepSeek-V2, DeepSeek-V3, and Seed1.5-VL technical reports, and listed among the authors of the Nature paper on DeepSeek-R1.

Research scientist at Google DeepMind in Mountain View working on machine learning, reinforcement learning, and robotics.

Research scientist at Meta GenAI in Menlo Park working on foundation models, language generation, and evaluation.

Research scientist at DeepSeek with public scholarly work on large language models and reasoning.

Qwen researcher and co-lead whose work focuses on pretraining and post-training, multimodal models, agent systems, and large-scale model infrastructure.

Research scientist at Google Research working on question answering, reasoning, and natural language processing.

Researcher and engineer at OpenAI, and a co-author of the GPT-4 Technical Report.

Research scientist at DeepSeek focused on LLM post-training, self-improvement, and reasoning.

Research engineer focused on large-scale machine learning and AI systems. He has worked at OpenAI and publishes writing and projects on his personal website.

DeepSeek researcher focused on large language models and reasoning who previously worked in Peking University's LANCO group.

Founder and CEO of Google DeepMind, leading AI research and product development; his work spans AI, neuroscience, game playing, and structural biology.

Research scientist at DeepSeek with public GitHub projects on large model systems and training.

Research scientist at DeepSeek with a public Google Scholar profile covering large language models and efficient inference.

Research scientist at DeepSeek with public GitHub work on reinforcement learning from human feedback and language models.

Research scientist at DeepSeek with public GitHub work on large language models and AI agents.

Jacob Morrison is a researcher whose work spans language model post-training, alignment, and evaluation. His public research page highlights projects including Tulu 2, Tulu 3, OLMo 2, and RewardBench.

Research scientist in Tongyi Lab whose official profile highlights post-training, reasoning, and coding large language models.

Research scientist at DeepSeek AI working on multimodal large language models and efficient multimodal alignment. Previously completed a PhD at Nanjing University focused on machine learning and computer vision.

Researcher working on speech and multimodal language models, including MiniMax-Speech and related speech understanding work.

Head of Safety Systems at OpenAI.

Research scientist at DeepSeek with public GitHub work spanning AI systems.

Research scientist at DeepSeek with public GitHub projects on AI systems.

Louis Martin is a scientist at Meta AI and a PhD student at McGill University and Mila. His research spans natural language processing and machine learning.

AI scientist at Mistral AI and PhD student at ENS Paris and CNRS. Her research focuses on language grounding, multimodality, and evaluation for multimodal and language models.

Research scientist in Tongyi Lab whose official profile highlights post-training, efficient reasoning, and multimodal large language models.

Lead of foundation models at MiniMax working on large language models, multimodal pretraining, and efficient training systems. He completed a PhD in computer science at Tsinghua University.

Research scientist at DeepSeek with public GitHub work on language models and AI systems.

Research scientist at Google Research whose public work spans multilingual and large-scale language modeling; arXiv author results include the PaLM paper.

Chief Scientist at Google DeepMind and Vice President of Research leading Gemini, with work spanning scalable sequence learning, large language models, games, and robotics.

Senior research scientist at Ai2 and affiliate associate professor at the University of Washington, with work spanning NLP, machine reading, and reasoning.

Research scientist at Mistral AI focused on efficient and robust machine learning, with interests including optimization, scaling laws, interpretability, and post-training.

Research scientist at Ai2 whose work focuses on natural language processing, semantic parsing, grounded language understanding, and question answering.

Research scientist at MiniMax AI Research interested in large language models, machine learning, and computer vision. He earned a PhD from Shanghai Jiao Tong University and previously worked at Alibaba DAMO Academy on vision-language reasoning and video understanding.

Researcher at DeepSeek AI interested in large language models and multimodal language models.

Rohan Anil is a research scientist at Google DeepMind. His public homepage highlights work on large language models, efficient machine learning systems, and multimodal AI.

Researcher affiliated with DeepSeek-AI on Google Scholar and coauthor of the DeepSeek technical reports.

Applied scientist at NVIDIA working on large language models, generative AI, and multimodal learning.

Senior research scientist in Tongyi Lab whose official profile highlights post-training, AI for science, evaluation and alignment, multimodal reasoning, and large language model reasoning.

Research scientist at Mistral AI and co-author of the Mistral 7B report.

Research scientist at MiniMax AI Research focused on large language models, machine learning, and recommendation systems. He received a PhD from Shanghai Jiao Tong University and previously worked at Alibaba DAMO Academy on machine learning and distributed databases.

Developer and researcher with public GitHub activity on DeepSeek-AI repositories including Janus and DeepSeek-VL2, plus coauthor credit on DeepSeek technical reports.

Researcher and co-author of the DeepSeek-V3, DeepSeek-V2, and DeepSeek LLM technical reports.

Research scientist at DeepSeek AI focused on reinforcement learning, multimodal models, and AI agents.

Researcher and co-author of the DeepSeek-V3, DeepSeek-V2, and DeepSeek LLM technical reports.

Vice President of Engineering and Research at Google and site lead for the Google Center in Israel; he also leads Search, Research, and AI for Crisis Response.

DeepSeek researcher and coauthor of the DeepSeek LLM, DeepSeek-V2, and DeepSeek-V3 technical reports.

Research scientist at MiniMax AI Research focused on reinforcement learning, reasoning, multimodal learning, large language models, and large-scale distributed systems. He received a PhD in machine learning from Carnegie Mellon University.

Research scientist at DeepSeek AI and co-author of the DeepSeek-V3, DeepSeek-V2, and DeepSeek LLM technical reports.

Florencia Leoni Aleman is an OpenAI contributor listed on the GPT-4V contributions page.

Y. Q. Wang is a DeepSeek contributor and co-author listed on the DeepSeek-V3 Technical Report.

OpenAI researcher and software engineer known for creating Triton, an open-source GPU programming language, and co-authoring the GPT-4 Technical Report.

Researcher and co-author of ByteDance Seed's Seed1.5-Thinking and Alibaba Qwen's Qwen3 Technical Report.

Research scientist at Google Research whose public work spans language modeling and multimodal generation; arXiv author results include PaLM and PaLM 2.

Researcher affiliated with DeepSeek on Google Scholar and coauthor of the DeepSeek-V2 and DeepSeek-V3 technical reports.

Research scientist at Meta working on machine learning, with interests in generative AI, multimodality, and helping models develop world understanding.

Senior research scientist at Ai2 and associate professor at Yale working on long-form language understanding, information retrieval, and scientific NLP.

Professor of Computer Science at the Hebrew University of Jerusalem and Visiting Faculty Researcher at Google, with work spanning algorithms, algorithmic economics, and AI-related decision systems.

Research scientist at Meta whose interests include natural language processing, multimodal AI, social computing, and computational social science.

Qwen researcher whose work spans language model alignment, multilingual models, and large-scale reasoning.

Research scientist at Meta working on large language models and coding assistants. He previously worked on pre-training language models and neural machine translation and completed a PhD in natural language processing at Sorbonne University.

Research scientist in Tongyi Lab whose official profile highlights post-training, efficient reasoning, and coding large language models.

Research scientist at DeepSeek with a public Google Scholar profile covering large language models and reasoning research.

Researcher at OpenAI working on frontier AI across coding, reasoning, post-training, and multimodal systems, with earlier work in accelerated computing and machine learning.

Researcher affiliated with DeepSeek on Google Scholar and coauthor of the DeepSeek LLM and DeepSeek-V2 technical reports.

Research scientist at DeepSeek with public GitHub projects spanning language models and AI systems.

Christopher Berner is an OpenAI contributor listed on the OpenAI GPT-4 contributions page.

Co-founder and research scientist at MiniMax AI Research. He received a PhD from Tsinghua University and works on foundation models, reinforcement learning, and data systems, with publications at major machine learning and NLP venues.

Researcher affiliated with DeepSeek on Google Scholar and coauthor of the DeepSeek-V2 and DeepSeek-V3 technical reports.

Faisal Azhar is a PhD candidate in computer science at Stanford University. His work focuses on multimodal systems that unify text, image, and speech, together with efficient training and inference for large-scale machine learning.

Research scientist in Tongyi Lab whose official profile highlights post-training and reasoning.

Research scientist at Z.ai focused on multimodal understanding and generation, reinforcement learning, AI agents, and end-to-end models. He received a bachelor's degree from Tsinghua University and a master's degree from Peking University.

Research scientist at DeepSeek AI working on reinforcement learning from verifiable rewards, reasoning models, and AI agents.

Machine learning researcher affiliated with DeepSeek on Google Scholar and coauthor of the DeepSeek-V2 and DeepSeek-V3 technical reports.

Research scientist on the Gemini team at Google DeepMind working on improving efficiency and accessibility in machine learning.

DeepSeek researcher and coauthor of the DeepSeek-V2 and DeepSeek-V3 technical reports.

Research scientist at DeepSeek with public scholarly work on large language models and efficient inference.

Researcher at DeepSeek AI and PhD in computer science at Peking University, focusing on large language models, multimodal large language models, and reinforcement learning.

Research scientist in Tongyi Lab whose official profile highlights multimodal understanding, image generation, and efficient large language models.

Research scientist at DeepSeek with public GitHub work on language models and AI systems.

Senior research scientist at Ai2 and affiliate assistant professor at the University of Washington.

Research scientist at DeepSeek with public scholarly work on large language models and AI systems.

Research scientist at DeepSeek with public scholarly work on large language models and reasoning.

Research scientist at Mistral AI working on multimodal models and reinforcement learning. He previously worked as a machine learning engineer and research scientist at Hugging Face.

Researcher affiliated with DeepSeek on Google Scholar and coauthor of the DeepSeek-V2 and DeepSeek-V3 technical reports.

Mahyar Babaei is a senior applied scientist at Microsoft. His public homepage highlights work on natural language processing, multilingual language models, and efficient AI systems.

Marie-Anne Lachaux is a research scientist at Meta whose public homepage highlights work on large language models, multilingual models, and speech.

Chief Research Officer at OpenAI.

Senior Staff Research Scientist at Google DeepMind working on language modeling, speech recognition, machine translation, and multimodal understanding.

Research scientist at DeepSeek with public scholarly work on language models and AI systems.

Research scientist at Alibaba's Tongyi Lab and a co-author of the Qwen3 and Qwen2.5 technical reports.

Research scientist at Meta whose work focuses on efficient large language models and multilingual NLP.

Machine learning engineer at Ai2 whose public work focuses on open language models, post-training, and evaluation.

Research scientist at OpenAI focused on multimodal models.

Research scientist in Tongyi Lab whose official profile highlights multimodal large language models, efficient training, and post-training.

Research scientist at DeepSeek with public scholarly work on large language models and AI systems.

Research scientist at Ai2 working on language model pre-training, adaptation, and alignment.

Research scientist at Moonshot AI whose homepage notes a Tsinghua PhD and research across machine learning, computer vision, and AI agents.

Research scientist at Alibaba Group and a co-author of the Qwen3 and Qwen2.5 technical reports.

Rishabh Kabra is a research scientist at Google DeepMind. His public homepage highlights work on machine learning systems and large-scale language model research.

DeepSeek researcher and coauthor of the DeepSeek-V2 and DeepSeek-V3 technical reports.

Researcher at DeepSeek interested in scalable and efficient learning, reinforcement learning, reasoning, and large-scale distributed training and inference.

Research scientist in Tongyi Lab whose official profile highlights post-training, multilingual large language models, and efficient reasoning.

LLM researcher at DeepSeek focused on alignment, post-training, and reasoning.

OpenAI engineer and researcher focused on infrastructure and silicon, credited on GPT-4 and GPT-4V for training execution, distributed training infrastructure, and hardware correctness.

Researcher affiliated with DeepSeek AI on Google Scholar and coauthor of the DeepSeek-V2 and DeepSeek-V3 technical reports.

Research Scientist at Moonshot AI.

Research scientist at MiniMax AI Research whose interests include large language models, machine learning, and code intelligence. He earned a PhD from Nanyang Technological University and previously worked on code intelligence, search, and recommender systems at Alibaba DAMO Academy.

Research scientist at MiniMax AI Research with interests in large language models, machine learning, and data intelligence. He earned a PhD from Nanyang Technological University and previously worked at Alibaba DAMO Academy on data intelligence and large language model applications.

Member of Technical Staff at DeepSeek.

Researcher affiliated with DeepSeek-AI on Google Scholar and coauthor of the DeepSeek-V2 and DeepSeek-V3 technical reports.

Staff research scientist at Google DeepMind in Cambridge, Massachusetts. His public profile says he works on translating human values and institutional constraints into tests and safeguards for foundation models.

Research scientist and GPT-4 coauthor known for work on generative modeling, diffusion methods, and machine learning systems.

Member of Technical Staff at Google DeepMind working on language and multimodal models.

Master's student at Peking University and research intern at OpenSeek and DeepSeek, with interests in large language models and natural language processing.

Researcher affiliated with Alibaba Group on Google Scholar and coauthor of the Qwen technical report.

DeepSeek researcher and coauthor of the DeepSeek-V2 and DeepSeek-V3 technical reports.

Research scientist at Z.ai with research interests in multimodal understanding and generation, large language models, and reinforcement learning. He received a bachelor's degree from the University of Science and Technology of China and a master's degree from Tsinghua University.

Researcher affiliated with DeepSeek on Google Scholar and coauthor of the DeepSeek-V2 and DeepSeek-V3 technical reports.

VP of Research at Google DeepMind and Professor of Information Engineering at the University of Cambridge, known for work in probabilistic machine learning and Bayesian statistics.

DeepSeek team member and co-author of the DeepSeek-V3 Technical Report.

Research engineer at OpenAI.

OpenAI team member and co-author of the GPT-4 Technical Report.

Researcher at OpenAI and a co-author of the GPT-4 Technical Report.

OpenAI team member and co-author of the GPT-4 Technical Report.

OpenAI contributor credited in the DALL·E 2 release and the GPT-4o System Card; a Google Scholar profile is publicly available.

Research scientist at Google DeepMind working on natural language understanding, generation, question answering, and evaluation, with current interests in multilinguality, attribution, and agent evaluation.

Research engineer on OpenAI's safety systems team. Previously studied at Carnegie Mellon University and is interested in safety, alignment, and evaluation of language models.

Research scientist focused on parallel and distributed machine learning systems.

Cohere researcher working on speech, multilinguality, multilingual speech, and speech translation, and a co-author of the Command A technical report.

Software engineer at OpenAI; previously worked at Palantir.

Researcher working on large language model training and evaluation, including PaLM 2.

Adrian Mollov is a machine learning engineer and researcher interested in generative models, large language models, reinforcement learning, and scalable multimodal systems; his profile notes experience at Google DeepMind.

Aimin Yang is a Moonshot AI contributor and co-author of Kimi k1.5: Scaling Reinforcement Learning with LLMs.

Assistant professor at the Mila-Quebec AI Institute and the University of Montreal, and Canada CIFAR AI Chair; her research focuses on vision-and-language and multimodal representation learning.

Product professional at OpenAI focused on models, products, and agents; previously led AI transformation and platform efforts at HubSpot.

Principal scientist at Cohere and adjunct associate professor at Columbia University working on reinforcement learning, active learning, and representation learning.

Research scientist at Google Research working on machine learning and natural language processing.

OpenAI contributor credited on the GPT-4 technical report.

Senior research scientist at Cohere Labs researching multilingual and multimodal large language models.

Senior Software Engineer at OpenAI. Previously studied computer science at the University of Waterloo.

Vice president of applied deep learning research at NVIDIA, leading work on foundation models, large language models, computer vision, robotics, and autonomous driving.

Google researcher whose publications include the PaLM 2 technical report and related work on multilingual language models and dialogue systems.

Alvin Wang is a software engineer at OpenAI focused on speech and audio. His official profile lists contributions to GPT-4.1, the audio models in the API, Sora, GPT-4, DALL-E 3, and Whisper.

Research Engineer at Ai2 on the OLMo team, focused on reliable and interpretable AI, transformers, retrieval, and autonomous agents.

Computer systems researcher and GPT-4 coauthor whose public work centers on networking and large-scale distributed systems.

AI researcher at Google DeepMind with interests in natural language processing, machine learning, and neuroscience.

Member of Technical Staff at OpenAI. Previously worked at Scale AI and studied computer science at Stanford University.

Author and communicator who led science communication work at OpenAI and helped present GPT-4; later continued working on AI communication and startups.

Software engineer at OpenAI whose official profile focuses on multimodal models and AI agents.

Researcher at OpenAI working on post-training and reasoning, after earlier research on self-supervised learning, reinforcement learning, and robotics.

Researcher working on large language model training and evaluation, including PaLM 2.

Anfeng Li works in AI model research at Alibaba DAMO Academy and is a co-author of the Qwen3 Technical Report.

Vice President of Global Affairs at OpenAI. Previously served in the U.S. government and in public policy leadership roles at Meta and Stripe.

Google researcher whose publications include the PaLM 2 technical report.

Machine learning engineer at Meta working on Llama post-training, with interests in reinforcement learning, generative AI, digital humans, AI at the edge, and ML systems.

Antoine Bosselut is an assistant professor in the Language Technologies Institute at Carnegie Mellon University. His research develops language technologies that align with people's social and cultural values and stay robust in realistic settings.

Research scientist at Cohere working on machine learning, computer vision, and explainable AI, including the Command A model family.

Machine learning researcher at Meta AI and visiting scientist at the University of Illinois Urbana-Champaign focused on language models and multimodal learning.

Research scientist at Cohere working on language modeling, reasoning, and vision.

Research scientist at NVIDIA working on foundation models, large-scale training, and model capabilities and safety.

Chief scientist at Mistral AI and former Meta researcher, known for work on multilingual and efficient foundation models.

Research scientist at OpenAI whose official profile highlights multimodal speech.

Research engineer at Ai2 focused on post-training and data for open language models.

Researcher affiliated with DeepSeek AI on Google Scholar and co-author of the DeepSeek LLM Technical Report.

Bahareh Hajishirzi is the Thomas J. Cable Endowed Professor at the University of Washington, senior director of NLP at the Allen Institute for AI, and a researcher working on NLP, computer vision, and machine learning.

NVIDIA researcher with a Google Scholar profile that includes the Nemotron-4 340B technical report.

DeepSeek researcher and coauthor of the DeepSeek LLM Technical Report.

Research scientist at Google DeepMind working on large-scale language models, multimodal learning, and efficient deep learning systems.

Product leader at OpenAI working on post-training, voice, and applied reasoning, after earlier product work on GPT-4V and developer products.

Engineer and infrastructure specialist who co-authored OpenAI scaling work and later joined Magic as a former OpenAI supercomputing lead.

Benjamin Mann is a machine learning researcher and engineer whose public homepage notes former work on GPT-3 and Codex at OpenAI and current work at Anthropic.

Researcher at OpenAI working on multimodal models, reinforcement learning, and AI safety.

Researcher whose public work spans NLP, reasoning, and evaluation; arXiv author results include OLMo and related language model work.

Senior research scientist at Google DeepMind working on natural language processing and multimodal representation learning.

OpenAI finance and accounting professional who was publicly credited on the GPT-4 technical report.

Binh Tang is an AI researcher at Meta. His public homepage highlights work in machine learning, natural language processing, and large-scale AI systems.

Research leader and GPT-4 coauthor who joined OpenAI in 2017 and later served as chief research officer after earlier engineering leadership work at Palantir.

Member of Technical Staff at OpenAI with a background in machine learning, computer vision, robotics, and cyber-physical systems.

Research scientist at DeepSeek with public work on large language models and reasoning.

Research scientist at Cohere working on machine learning and reinforcement learning.

Research scientist at OpenAI designing language environments and agents; previously built peer-to-peer applications and holds a PhD from Oxford.

Strategy and operations leader at OpenAI whose official profile highlights interests in learning, biology, and language.

Research engineer at Google DeepMind and PhD candidate at UC Berkeley working on multimodal understanding, reasoning, and agentic systems.

Research scientist at Meta working on post-training, alignment, and reinforcement learning for language and multimodal models.

Research scientist at OpenAI whose official profile highlights multimodal speech and audio.

Software engineer at OpenAI. Previously studied electrical engineering and computer science at the University of California, Berkeley.

OpenAI contributor credited on the GPT-4 technical report.

Researcher focused on speech AI, computer vision, and audio-visual learning. He has worked at OpenAI and publishes publications and projects on his personal website.

Professor at Carnegie Mellon University whose public research spans machine learning and natural language processing; arXiv author results include the PaLM paper.

Research scientist at OpenAI whose official profile highlights multimodal reasoning and agents.

Research engineer at OpenAI working on AI agents and coding systems. Previously worked on data and product efforts at Stripe and studied computer science and philosophy at Harvard University.

Research scientist at DeepSeek with public work on language models and multimodal learning.

Research scientist in Tongyi Lab whose official profile highlights coding large language models and AI agents.

Research scientist in Tongyi Lab whose official profile highlights post-training, efficient reasoning, and multilingual large language models.

Researcher at OpenAI working on reasoning, multimodal systems, and products that make AI more useful in everyday life.

Software engineer at OpenAI whose official profile focuses on speech and audio.

Research scientist at Ai2 working in NLP and machine learning, with interests in efficient training, pruning, and sparsity.

Member of Technical Staff at OpenAI working on reliability engineering. Previously worked on software in cloud, AI, and hardware, and earned a BSE in computer systems engineering from Arizona State University.

Applied scientist at Amazon working on large language models, responsible AI, and evaluation for foundation model systems.

Google researcher whose publications include the PaLM 2 technical report.

Research scientist at Meta working on reinforcement learning and generative models. His homepage highlights robotics, computer vision, and simulation, alongside work related to Llama 3.

Engineering manager at OpenAI with a background in privacy and security engineering across biotech, payments, and advertising.

Member of Ai2's data team interested in data management systems and workflow tooling for research and model development.

Research scientist at Google Research focused on natural language processing and machine learning.

Research engineer at Meta on the large language models team and honorary research fellow at the UCL Centre for Artificial Intelligence. His work focuses on language model scaling laws and transformer architecture.

Former OpenAI governance researcher and GPT-4 coauthor known for AI forecasting and alignment writing.

Daniel M. Ziegler is a research scientist at OpenAI whose public homepage highlights work on large language models, reinforcement learning from human feedback, and alignment-related research.

Research scientist at OpenAI focused on machine learning and theorem proving.

Investor and advisor at OpenAI; previously on the management team at Stripe.

OpenAI contributor credited for business strategy and investor relations support on GPT-4.

Principal Scientist at Google DeepMind focused on machine learning systems and AI research.

Research scientist at Cohere whose public OpenReview profile lists interests in natural language processing, efficiency, and large language models.

Researcher at OpenAI working on multimodal systems, post-training, and evaluations, with earlier work across 3D, computer vision, and embodied AI.

Research scientist at Google Research working on large language models, natural language processing, and multi-agent systems.

Research scientist at NVIDIA and assistant professor at NYU, working on machine learning, deep learning, and robotics.

Research scientist at Ai2 whose work focuses on open language models and multimodal systems.

Vice President of Product at Google DeepMind and head of the Google DeepMind product team.

Works at OpenAI.

OpenAI staff contributor whose public research profile links her work across public policy and frontier evaluations at OpenAI, following earlier operations leadership at OpenResearch.

Google researcher whose public profile lists work across machine learning, natural language processing, and generative AI.

Senior machine learning researcher at Cohere working on pretraining, post-training, and safety for large language models, according to her public OpenReview profile.

Final-year PhD candidate at the University of Washington whose public research focuses on evaluation, uncertainty, and multimodal grounding in language models; her arXiv author results include OLMo and OLMES papers.

Researcher working on open language models and multimodal systems, including Gemma.

Research scientist at OpenAI focused on machine learning, multimodal world models, and representation learning.

Researcher at NVIDIA working on computer architecture, machine learning, and large language models, including Nemotron-4.

Research scientist at Cohere working on reasoning, simulation, and agentic AI.

Research scientist in Tongyi Lab whose official profile highlights post-training, efficient reasoning, and large multimodal models.

Research scientist at Google DeepMind in Cambridge working on large language models and generative AI.

Member of Technical Staff at OpenAI focused on data quality, data curation, and training methods for frontier models.

Researcher affiliated with Alibaba Group on Google Scholar and coauthor of the Qwen3 technical report.

Principal applied scientist in Amazon AGI whose publications include the Amazon Nova Premier technical report.

Security engineer at OpenAI with a background in network and information security, including prior work at Nmap, Mayo Clinic, and CENSUS.

Software engineer at OpenAI whose official profile focuses on data and evaluations for language models.

Gabriel Bernadett-Shapiro is an OpenAI contributor listed on the OpenAI GPT-4 contributions page.

Research scientist and writer at OpenAI who works on the societal impact and interpretability of advanced AI systems.

Research scientist in Tongyi Lab whose official profile highlights post-training, reinforcement learning, reasoning, and AI agents.

Researcher whose public work focuses on retrieval, question answering, and large language models; arXiv author results include the LLaMA paper.

Researcher working on enterprise language models and multilingual systems, including Cohere Command A and Aya.

Research scientist at Google DeepMind focused on machine learning, optimization, computer vision, and AI for science.

Haiming Bao is an OpenAI contributor listed on the OpenAI o1 contributions page.

Researcher working on enterprise and multilingual language models, including Cohere Command A.

Researcher at NVIDIA working on computer vision, machine learning, and 3D vision, including Nemotron-4.

Product manager at OpenAI working on bringing AI models into products, after earlier product and go-to-market work at Spotify and Soundtrap.

Research scientist working on generative AI and multimodal intelligence.

Google researcher whose public profile lists work across data management, distributed systems, data mining, human-computer interaction, and natural language processing.

Research scientist at Meta FAIR working on language modeling, generalization, reasoning, and AI agents.

Jade Leung leads OpenAI's work on frontier model policy, governance, and partnerships. She was formerly a Governance and Public Policy fellow at the University of Oxford.

Chief Scientist at OpenAI. Previously served as Director of Research at OpenAI and studied computer science at the University of Warsaw.

Research scientist at Google DeepMind working on large language models, multimodal models, and language design.

Research scientist at Cohere with research interests in computer vision, multimodal learning, and model editing.

Google researcher whose publications include the PaLM 2 technical report.

Research scientist at Cohere working on language models, post-training, and evaluation.

Staff research engineer at Google DeepMind working on language models and technical infrastructure.

Software engineer at OpenAI whose official profile highlights reinforcement learning, robotics, and AI for health.

Researcher working on large language models and enterprise NLP systems, including Cohere Command A.

Jeff Belgum is an OpenAI contributor listed on the DALL·E 2 preview contributions page.

Staff software engineer at Google DeepMind interested in systems and applied machine learning.

Founding engineer at Galactica and former staff software engineer at OpenAI.

Research scientist at OpenAI whose official profile focuses on multimodal speech.

Qwen researcher whose work focuses on alignment, reasoning, and multilingual large language models.

Researcher working on large language models and multimodal systems, including NVIDIA Nemotron-4.

Research scientist at Google working on efficient AI models for mobile devices and ML systems, with interests in systems, algorithms, and co-design.

Researcher at DeepSeek focused on large language models, multimodal systems, and AI agents.

Research scientist in Tongyi Lab whose official profile highlights post-training and multimodal large language models.

Leading model behavior and product at OpenAI. Previously worked on generative AI at Instacart and as a product lead at Meta.

Research scientist at Cohere Labs and technical lead of the multimodal team.

OpenAI contributor focused on security applications of large language models; public author and event pages identify Joel Parish as a security staff member at OpenAI.

AI research engineer at OpenAI focused on reinforcement learning, and co-author of the GPT-4 Technical Report.

Jonathan Tow is a research scientist at Cohere whose public profile highlights work on efficient large language model adaptation and finetuning. He is known as the lead author of QLoRA and works on practical methods for training and aligning language models.

Research scientist at OpenAI working on general intelligence; previously studied at Princeton University and Williams College.

Member of technical staff at OpenAI who worked on CLIP and Whisper; previously a PhD student in computer science at NYU.

Founding member of OpenAI's alignment team. Public profile notes prior software engineering work at Google.

Researcher working on large language model training and evaluation, including PaLM 2.

Product and engineering leader who worked on GPT-4, ChatGPT Enterprise, and advanced data analysis at OpenAI. He later became CTO of Khan Academy.

Research Scientist at Google working on making language models more factual and controllable.

Research scientist at Google DeepMind working on natural language processing and machine learning systems.

Google researcher whose publications include the PaLM 2 technical report.

Member of Technical Staff at OpenAI whose interests include complex systems, AGI safety, and computation. Previously worked at Meta and Morgan Stanley and studied Economics and Computer Science at Harvard.

Research scientist at DeepSeek with public scholarly work on large language models and reasoning.

Research scientist at Google DeepMind in Seattle.

Research scientist at NVIDIA working on computer vision, deep learning, and reinforcement learning.

Research engineer at Ai2 working on open language models, machine learning systems, and evaluation.

Research engineer at Google DeepMind whose research interests include computer vision, geometric deep learning, and generative models.

Research scientist at Google DeepMind working on natural language generation, multimodality, and on-device machine learning.

Machine learning researcher at Meta focused on Llama model adaptation, post-training, and data-centric learning.

Staff Research Engineer at OpenAI working on language modeling and reasoning.

Research scientist at OpenAI focused on multimodal language and large language model alignment.

Research scientist at Ai2 working on large language models, machine learning with human feedback, and related topics; previously at Stanford and MIT.

Research scientist at Cohere working on language modeling, agents, reasoning, safety, and post-training.

Research scientist at Meta FAIR working on multimodal and speech-language AI; his personal site highlights projects including the Large Concept Model family.

Research scientist at DeepSeek with public work on large language models and reasoning.

Member of technical staff at OpenAI.

Vice President of Global Affairs at OpenAI and a co-author of the GPT-4 Technical Report.

Lauren Workman is a research scientist at OpenAI working on deep learning, robotics, and multimodal AI. Her official profile lists contributions across GPT-4.1, o3 and o4-mini, GPT-4o, robotics, and DALL-E 3.

Research scientist at NVIDIA working on machine learning, natural language processing, and vision-language models, including the NVLM project.

Research scientist at Google DeepMind in London working on efficient, robust, and reasoning-capable language models. His homepage also notes interests in language model alignment and a mathematics background from Cambridge.

Research scientist at Google Research working on large language models, natural language understanding, and reasoning.

Researcher with public work on fairness, robustness, and language technologies. Public profiles connect her research to both UNC Charlotte and Amazon.

Applied scientist at Amazon working on large language models, multimodal AI, and audio generation.

Research scientist at Cohere working on machine learning and natural language processing, including the Command A model family.

Luca Soldaini is a principal research scientist at Cohere who leads the data team and works on data provenance and training more trustworthy language models.

Research scientist and engineer whose public work spans deep learning, language models, and efficient inference.

Leader of Qwen's reasoning and agent team.

Member of Technical Staff at OpenAI with interests spanning AI for education, machine learning, and human-computer interaction.

Researcher working on foundation models and agentic systems, including Amazon Nova Premier.

Product designer at OpenAI whose official profile explores human-computer interaction.

Research scientist at Google DeepMind whose public profiles describe work in machine learning and generative modeling, with a personal homepage covering neural networks, variational inference, and program synthesis.

Matt Gardner is a machine learning researcher at Ai2 working on language models, reasoning, and scientific approaches to NLP. His public profile highlights open language model development, evaluation, and research infrastructure.

Matthew Botvinick is a Google DeepMind scientist whose public profile focuses on neuroscience-inspired AI, cognitive science, and machine learning.

Research scientist at Google working on large-scale language models and natural language processing.

Technical and creative leader who has worked across games, startups, and AI products. He has held engineering and product roles at OpenAI and previously worked in the Los Angeles games industry.

Member of technical staff at OpenAI whose official profile focuses on deep learning, robotics, and speech.

Melanie Subbiah is an independent AI researcher based in New York City. Her work focuses on language and multimodal AI, especially commonsense reasoning and communicative behavior.

Research scientist at Google Research working on machine learning and natural language processing.

Research scientist at Google DeepMind working on AI for language.

Research scientist at Ai2 whose interests include natural language processing, machine learning, and computer vision.

Research engineer at Google DeepMind working on large language models and generative AI.

Research scientist at Cohere focused on language modeling, post-training, and multimodality.

Mikhail Chernyshev is a systems engineer focused on efficient distributed systems for large-scale deep learning, spanning compiler stacks, networking, operating systems, and hardware.

Engineer and researcher at OpenAI working on multimodal models, after earlier product work on Facebook's iPhone, iPad, and Messenger apps.

Applied scientist in Amazon AGI whose publications include the Amazon Nova Premier technical report.

Senior principal scientist at Amazon AGI focusing on efficient training and inference of foundation models, large language models, and multimodal models.

Morgan Grafstein is a software engineer and artist at OpenAI. His personal site says his work spans hardware, software, and rendering.

Director of engineering at NVIDIA working on machine learning, computer vision, and agentic AI systems.

Research scientist at Google DeepMind working on robot learning, real-world robotics, and reinforcement learning.

Research scientist at NVIDIA working on training large language and multimodal models.

Mustafa Hajij is a research scientist at Ai2 and an adjunct professor in the Department of Computer Science at the University of Southern Maine. His research spans graph machine learning, geometric learning, and applied mathematics.

Namit Katariya is a computer science PhD student at Stanford University. His interests include large-scale machine learning, natural language processing, ranking, and recommendation systems.

Staff software engineer at Google specializing in machine learning model development and performance optimization for TPUs and other accelerators.

Research scientist and research director at Google DeepMind working on machine learning for health, sustainability, and human-centered AI.

Ngoc-Quan Pham is a research scientist at Cohere whose work spans large language models, natural language generation and understanding, multimodal learning, continual learning, and transfer learning.

Researcher at NVIDIA working on computer vision and machine learning, including large language model work such as Nemotron-4.

Engineer at OpenAI whose official profile focuses on compute systems and inference.

Research Scientist at Google DeepMind focused on post-training large language models and evaluation.

OpenAI contributor credited on the GPT-4 technical report; his personal website describes interests in machine learning, software engineering, and data visualization.

Research engineer whose public work spans language models and multimodal systems; arXiv author results include the Llama 2 paper.

NVIDIA researcher with a Google Scholar profile that includes the Nemotron-4 340B technical report.

Member of Technical Staff at OpenAI and co-author of the GPT-4 Technical Report.

Google researcher and engineer best known as a co-inventor of the Transformer and a contributor to systems including T5, LaMDA, and Gemini.

Oleg Boiko is an OpenAI contributor listed on the OpenAI GPT-4 contributions page.

Research scientist at OpenAI and contributor to the o1 reasoning launch.

Researcher working on large language model scaling and evaluation, including Google PaLM.

Software engineer at OpenAI whose official profile focuses on multimodal models.

Research scientist at NVIDIA working on large language model training and machine learning systems.

Petar Veličković is a Senior Staff Research Scientist at Google DeepMind and an affiliated lecturer at Cambridge. His research explores building general-purpose reasoning agents by combining inference, search, and learning.

Postdoctoral researcher at FAIR with interests in multilingual and multimodal language models, including work associated with Llama 2.

OpenAI infrastructure leader focused on industrial compute, large-scale AI systems, and strategic buildout of compute and energy capacity.

J. Michael Pokorny is a software engineer at OpenAI focused on inference. His official profile lists contributions to GPT-4.1, the Realtime API, API cost optimizations, GPT-4o, and gpt-oss.

Praneet Dutta is a researcher affiliated with Cohere whose publications focus on large language models and related model development work.

Associate Professor at the University of Pennsylvania working on machine learning, optimization, and large-scale AI systems.

Researcher currently at UC Berkeley whose homepage notes prior work at Cohere on pretraining and post-training for large language models.

Research scientist at Google working on speech, language, and multimodal machine learning systems.

Scientist and engineer at OpenAI working to build AGI that benefits all of humanity.

Research scientist at Google Research known for large-scale deep learning and language models; arXiv author results include the PaLM 2 technical report.

Rachel Lim is a technical staff manager at OpenAI focused on speech and audio. Her official profile lists contributions across GPT-4.1, ChatGPT search, deep research, the audio models in the API, GPT-4o mini, GPT-4.5, and GPT-4.

Research scientist at Google DeepMind interested in large language models, efficient transformers, AI for coding, and AI4Mat.

Research scientist at OpenAI working across computer vision, robotics, and language.

Research scientist at Google Research focused on machine learning and natural language processing, including text generation and summarization.

Research scientist at Google Research and professor at Tel Aviv University whose work spans machine learning, optimization, and natural language processing.

Research scientist at NVIDIA working on large language models and natural language processing.

Engineer and founder focused on AI products, developer tools, and startup building. He has worked at OpenAI, Meta, Google, and Palantir and later founded Zephyr and Humanity Health.

Rewon Child is a machine learning researcher whose public homepage notes previous work at OpenAI and current work on developer tools. His public research profile highlights sparse transformers and generative modeling.

Google researcher whose publications include the PaLM 2 technical report.

Robin Sikand is a machine learning researcher at Google working mostly on large language models.

DPhil student in robotics and AI at the University of Oxford and Rhodes Scholar interested in the safe deployment of autonomous systems.

Software engineer at OpenAI whose official profile focuses on speech and audio.

Researcher at Tencent Hunyuan with public publications on large language models, multimodal systems, and efficient post-training, including Hunyuan-Large, LLaVA-Video-R1, and Rest-R1.

Chief Global Affairs Officer at OpenAI.

Systems engineer at OpenAI working on production AI systems.

Research engineer at Ai2 working on open language models, post-training, evaluations, and data.

PhD student in EECS at UC Berkeley advised by David Wagner and Jacob Steinhardt, with research focused on trustworthy machine learning and AI safety.

Researcher at Microsoft working on large-scale deep learning systems and efficient training infrastructure.

Research scientist at Meta working on large language models, foundation models, and reasoning.

Research scientist at Google DeepMind in Mountain View focused on AI red teaming, post-deployment risk management, and language model evaluation. She previously worked in cyber policy and software engineering and earned a PhD from the NYU Center for Data Science.

Researcher whose public work focuses on AI safety, alignment, and governance.

Research scientist at Google DeepMind working on large language models and artificial intelligence, based on his public OpenReview profile.

Physician-scientist and machine learning researcher at OpenAI with work in AI for healthcare.

Incoming assistant professor in Carnegie Mellon's School of Computer Science and current research scientist at Meta AI, working on long-context language models and reasoning.

Researcher at Cohere working on machine learning and natural language processing, including the Command A model family.

Shane Lyu is a PhD student in Electrical and Computer Engineering and Machine Learning at Carnegie Mellon University. He is advised by Ruslan Salakhutdinov and Viraj Prabhu and works on machine learning research.

Researcher at OpenAI focused on reasoning, agency, and post-training to make AI systems more useful.

Sheila Dunning is an operations leader at OpenAI whose official profile focuses on helping research, governance, and safety teams work effectively. Her public contributions page lists work across GPT-4.1, the Preparedness Framework, safety and policy efforts, and GPT-4.

Research scientist in Tongyi Lab whose official profile highlights post-training, large language models, and AI agents.

Researcher affiliated with Alibaba Group on Google Scholar and coauthor of the Qwen3 technical report.

Senior research scientist at Google DeepMind in Zurich working on the Gemini team.

Research scientist on the Alibaba Qwen Team and co-author of the Qwen Technical Report.

Research scientist at Mistral AI.

Research scientist at Ai2 whose research interests include language grounding and visual understanding.

Research scientist at Meta FAIR focused on language models, retrieval, and data curation. He joined FAIR in 2023 after spending five years at AI2.

Research scientist at NVIDIA with interests in machine learning systems, deep learning, and distributed systems.

Staff research engineer at Google DeepMind in London working on the Gemini team.

Research scientist at OpenAI working on reasoning, code generation, and interpretability.

Communications leader at OpenAI, after earlier communications leadership roles at Apple.

Research scientist at Google DeepMind working on machine learning and large language models.

Engineer at OpenAI focused on software and hardware systems.

Member of technical staff at OpenAI and co-author of the GPT-4 Technical Report.

Economist and researcher at Anthropic working on the economics of transformative AI and broader questions about AI progress and impact.

Research scientist at OpenAI working on AI safety; previously a graduate student at UC Berkeley studying machine learning and neural signal processing.

Research scientist at Cohere focused on long-context language models and efficient training.

Member of technical staff at OpenAI whose official profile highlights multimodal models, audio, and video.

Software engineer at OpenAI.

Thibault Biervoye is a Research Scientist at Google DeepMind focused on large language models, memory-augmented transformers, and knowledge transfer.

Research scientist at Meta working on multimodal foundation models and open-source AI. His homepage says he leads multimodal efforts at Meta AI and contributes to open-source model releases.

NVIDIA researcher with a Google Scholar profile that includes the Nemotron-4 340B technical report.

Research scientist in Tongyi Lab whose official profile highlights post-training, reasoning, and large multimodal models.

Researcher at Cohere in Toronto working on large language models.

Machine learning researcher and engineer working on large-scale AI systems, and a co-author of the PaLM 2 technical report.

Senior applied scientist at Amazon AGI focused on multimodal deep learning and computer vision, especially video generation, diffusion, and representation learning.

OpenAI researcher and software engineer based in San Francisco, and co-author of the GPT-4 Technical Report.

Researcher at OpenAI and incoming applied scientist at Anthropic. Previously studied mathematics and machine learning and worked on reinforcement learning and alignment research.

Research scientist at Mistral AI working on efficient training and low-latency inference for large models.

Tomer Ronen is a research scientist at Cohere Labs whose work focuses on efficient training and fine-tuning of large language models, natural language processing, and applications in genomics and biology.

Research scientist at DeepSeek working on deep learning, large language models, multimodal systems, and trustworthy machine learning.

Research scientist at Ai2 working on efficient and transparent large language models.

Senior researcher at OpenAI whose official profile focuses on AI robustness and the future of compute.

Google researcher whose publications include the Gemma 2 technical report.

William Zhuk is an OpenAI contributor credited on the GPT-4 Technical Report and listed on the OpenAI GPT-4 contributions page.

Researcher and co-author of the DeepSeek-V3 Technical Report.

Xiao Wang is a Moonshot AI contributor and co-author of Kimi k1.5: Scaling Reinforcement Learning with LLMs.

Research scientist in Tongyi Lab whose official profile highlights reasoning, large-scale reinforcement learning, and multilingual large language models.

Developer and researcher with public GitHub activity on DeepSeek-AI repositories including DeepSeek-V3 and DeepEP, plus coauthor credit on the DeepSeek-V3 technical report.

Research scientist at Cohere and associate at Harvard Business School whose work focuses on natural language processing and multimodal machine learning.

Xixuan Song is a Moonshot AI contributor and co-author of Kimi k1.5: Scaling Reinforcement Learning with LLMs.

Software engineer at Google DeepMind interested in machine learning, applied mathematics, and scalable systems.

Research scientist in Tongyi Lab whose official profile highlights post-training, efficient reasoning, and multilingual large language models.

Computer scientist whose public work focuses on natural language processing, commonsense reasoning, and multimodal AI.

Member of Technical Staff at DeepSeek.

Researcher affiliated with DeepSeek on Google Scholar and coauthor of the DeepSeek-V2 technical report.

Yingtao Zhang is a Moonshot AI contributor and co-author of Kimi k1.5: Scaling Reinforcement Learning with LLMs.

Ying Zhang is a senior applied research scientist on NVIDIA's foundation model team.

Researcher working on large language models and enterprise NLP systems, including Cohere Command A.

Researcher working on large language model training and evaluation, including PaLM 2.

Final-year PhD student at Peking University and research intern at DeepSeek AI, focusing on machine learning and large language models.

Researcher affiliated with DeepSeek-AI on Google Scholar and coauthor of the DeepSeek-V3 technical report.

Vice President and Research Science Manager at Meta whose work spans artificial intelligence, machine learning, computational game theory, and behavioral economics.

Software engineer at Google DeepMind and PhD student at UCLA focusing on efficient large language models.

Research scientist at Google working on large language models, AI agents, systems for machine learning, and optimization.

Yuchen He is a technical staff manager at OpenAI focused on speech and audio. His official profile lists contributions across GPT-4.1, the audio models in the API, Sora, GPT-4, DALL-E 3, and Whisper.

Research scientist at Google Research focused on language and multimodal models, with interests spanning natural language processing, computer vision, and speech.

Associate professor at Carnegie Mellon University whose public research spans NLP and machine learning; arXiv author results include OLMo and related open language model work.

Research scientist at Google DeepMind working on post-training, alignment, and multilinguality.

Staff Research Scientist at Google DeepMind working on foundation models for language, speech, and multimodal systems.

Applied research scientist at Moonshot AI Labs working on large language model reasoning and multimodal systems.

AI researcher at DeepSeek focused on reasoning and large language models, based on his public homepage and DeepSeek authorship context.

Zejiang Shen is a research scientist at the Allen Institute for AI whose interests include representation learning, generative AI, and multimodal learning.

Research Scientist at Alibaba Group, Qwen Team.

PhD student in computer science at Stanford University working on natural language processing and machine learning.

Research scientist in Tongyi Lab whose official profile highlights multimodal reasoning, agentic reinforcement learning, and post-training for large language models.

Researcher and co-author of the DeepSeek-V3 Technical Report.

DeepSeek researcher and coauthor of the DeepSeek-V3 technical report.

Researcher affiliated with DeepSeek AI on Google Scholar and coauthor of the DeepSeek-V3 technical report.

Member of technical staff at Cohere Labs working on reinforcement learning and post-training for language models and agents.

Zora Tung is a Research Scientist at Google DeepMind.

Luca Soldaini

Kyle Richardson

Yukun Zha

Matei Zaharia

Hamish Ivison

Joost Huizinga

Shantanu Jain

Tim Brooks

Xinyu Zhang

Kaustubh Jha

Tong Wu

Junyang Lin

Pradeep Dasigi

Utku Evci

David Brandfonbrener

Ilge Akkaya

Zihan Wang

Shyamal Anadkat

Le Yu

Haoyu Lu

Adrià Garriga-Alonso

Adrien Ecoffet

Valentina Pyatkin

Siddhartha Brahma

Xiaohuan Zhou

Xin Hu

Bowen Yu

Tao Xu

Tomer Kaftan

Carroll Wainwright

Hao Zhang

Trevor Gale

Jerry Tworek

Leon Derczynski

Brandon McKinzie

Juntang Zhuang

Yufei Guo

Arka Dhar

Dan Roth

Evgenia Rusak

Mitesh M. Khapra

Trung H. Bui

Alec Radford

Seungyoun Hong

Jiatao Gu

Sydney Z. Li

Roger Jiang

Shuai Bai

Josh Achiam

Isaac MacMillan

Carl Ble

Boris Ginsburg

Sebastian Gehrmann

Amelie Haghighat

Ana Klimovic

Uday Bondhugula

Yuning Mao

Runxin Xu

Hao Yang

Yizhong Wang

Thomas B. Brown

Boris Ivanovic

Geri Skenderi

Hugo Touvron

Chunting Zhou

Dayiheng Liu

Yichang Zhang

Yuling Gu

Aakanksha Chowdhery

Hyung Won Chung

Shanghao Lu

Steven Adler

Wangding Zeng

Ameet Talwalkar

Rowan Zellers

Slava Petrov

Yuntian Deng

Arvind Neelakantan

Brian Lester

Chunlin Li