OpenAI

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.

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.

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.

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.

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.

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.

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 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 OpenAI whose public profiles describe work on generative AI and reinforcement learning, after PhD study at the University of Cambridge.

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

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.

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.

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

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.

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.

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.

Researcher and engineer focused on AI systems, applications, alignment, and interpretability; contributed to OpenAI reasoning-model system-card work.

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.

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.