NVIDIA

Mona Jalal is a computer vision research engineer at Toyota Material Handling. Her homepage says she leads 3D computer vision work such as 6D object pose estimation and synthetic data generation, previously worked as an R&D engineer at UC Berkeley's FHL VIVE Center, completed doctoral study in computer vision at Boston University, and earlier earned master's degrees in computer sciences and electrical engineering from the University of Wisconsin-Madison.

Ming-Yu Liu is a vice president of research at NVIDIA and an IEEE Fellow. He leads the Deep Imagination Research group, which focuses on deep generative models for content creation and foundation models for physical AI. He previously held research leadership roles at Mercedes-Benz Research and Development North America and National Tsing Hua University, and he earned degrees from National Taiwan University, National Chiao Tung University, and the University of Illinois Urbana-Champaign.

Arash Vahdat is a research director at NVIDIA Research, where he leads the GenAIR team on fundamental generative AI research. Before joining NVIDIA, he was a research scientist at D-Wave Systems and a research faculty member at Simon Fraser University, where he led video analysis research and taught machine learning for big data. He earned a PhD in computing science from Simon Fraser University.

Dilek Hakkani-Tur is a Professor of Computer Science at the University of Illinois Urbana-Champaign and an Amazon Scholar at Amazon Health Science. Her UIUC faculty profile says her research interests include conversational AI, natural language and speech processing, spoken dialogue systems, and machine learning for language processing.

Kartikeya Mangalam is a PhD student in computer vision at UC Berkeley advised by Jitendra Malik. His public homepage says he previously held a visiting researcher role at Meta AI, studied in Stanford CS, graduated summa cum laude in electrical engineering with a machine learning minor from IIT Kanpur, and works on computer vision, video understanding, and human motion analysis.

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.

Researcher at OpenAI focused on data-centric methods for foundation models, including synthetic data and reinforcement learning. Previously a research scientist at Meta GenAI; earned BS, MS, and PhD degrees in computer science at Stanford.

Utku Evci is a researcher at Google. His public Google Research profile describes work on making neural network training faster and more efficient, with public materials centered on sparsity, transfer learning, and machine intelligence.

Chinmay Hegde is an associate professor at the NYU Tandon School of Engineering. His public homepage and NYU faculty profile say he works on machine learning, optimization, and inverse problems, joined NYU in 2021 after three years at Iowa State University, previously completed a postdoc at Stanford University, and earned a PhD in electrical and computer engineering from Georgia Tech in 2016.

Researcher at NVIDIA Research. Previously a PhD student in Computer Science and Engineering at HKUST, with earlier internships at International Digital Economy Academy and Microsoft Research.

Public profiles say he completed a Georgia Tech PhD in 2025 after earlier study at Rice and USTC, and his current work focuses on bringing frontier AI to everyday devices.

Sanjiv Kumar is a Google Fellow and vice president at Google Research. His public homepage says he leads teams working on large machine learning foundation models and generative AI, has spent more than 25 years building machine learning systems and products, and received a PhD in computer science from Carnegie Mellon University in 2005.

Machine learning researcher focused on scalable learning and generative modeling, known for work on variational autoencoders, Adam, Glow, and variational diffusion models; his homepage says he is currently at Anthropic.

Ming Lin is a professor of computer science at the University of Maryland, College Park and the chief executive officer and co-founder of Aitrios.ai. Her public homepage says she was the founding director of the GAMMA lab, previously served as assistant dean of the University of Maryland's Institute for Advanced Computer Studies, and earned her BS, MS, and PhD in EECS from the University of California, Berkeley.

Junxian He is an assistant professor in computer science and engineering at the Hong Kong University of Science and Technology. His public homepage and Princeton profile say he works at the intersection of natural language processing and machine learning, focusing on scalable methods for language model training and reasoning, completed a PhD in computer science at Princeton University in 2024, and previously earned bachelor's degrees in economics and computer science from Peking University.

NVIDIA Research and Wonmin Byeon's personal site identify him as a researcher at NVIDIA Research in California. Public site materials describe interests in computer vision, robotics, recurrent and state-space models, sequence learning, and spatio-temporal learning.

Zihan Liu's public homepage describes him as a senior research scientist at NVIDIA ADLR working on LLM reasoning, post-training, and retrieval-augmented generation.

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.

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.

NVIDIA's research page describes Jan Kautz as vice president of Learning and Perception Research, working across computer vision, machine learning, computational photography, and geometric vision.

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.

Abhinav Khattar is a research scientist at NVIDIA working on LLM alignment, customization, and machine translation. Before joining NVIDIA, he earned a master's degree in computer science from Carnegie Mellon University and worked on information retrieval and speech recognition.

Vahid Noroozi is an applied research scientist at NVIDIA. His NVIDIA author profile says his work focuses on deep learning for speech and natural language processing and that he received a PhD in computer science from the University of Illinois Chicago. His homepage says he previously worked on post-training large language models at Google DeepMind after earlier multimedia and neuroscience research at TU Delft and the Max Planck Institute for Biological Cybernetics.

OpenReview lists Grace Lam as a researcher at NVIDIA after prior work at Google, with study at Stanford and MIT. NVIDIA public pages connect her to Cosmos Policy for robot control and Nemotron-Cascade 2 for LLM post-training.

Mona Jalal

Ming-Yu Liu

Arash Vahdat

Dilek Hakkani-Tur

Kartikeya Mangalam

Matei Zaharia

Sang Michael Xie

Utku Evci

Chinmay Hegde

Hao Zhang

Yonggan Fu

Sanjiv Kumar

Diederik P. Kingma

Ming Lin

Junxian He

Wonmin Byeon

Zihan Liu

Trevor Gale

Leon Derczynski

Jan Kautz

Mitesh M. Khapra

Abhinav Khattar

Vahid Noroozi

Grace Lam