Anthropic

Amanda Askell is a philosopher and AI alignment researcher at Anthropic. Her personal site says she previously worked as a research scientist on the policy team at OpenAI.

Research scientist at Anthropic who leads the Societal Impacts team and works on AI evaluation, alignment, and societal impacts.

Tom Henighan works on large language model interpretability at Anthropic. He previously worked on scaling laws at OpenAI and machine learning engineering at Beehive AI, and he studied physics at Stanford after graduating from Ohio State University in 2010 with a degree in English, mathematics, and philosophy.

Aengus Lynch is a fifth-year PhD student in machine learning at Carnegie Mellon University advised by Zico Kolter. His homepage says he works on control, reinforcement learning, games, and machine learning, and his CV shows research internships at Anthropic and Google DeepMind after completing a BASc in engineering physics at the University of British Columbia.

Evan Hubinger is Head of Alignment Stress-Testing at Anthropic, where he works on AI safety and alignment. He previously worked at MIRI and OpenAI, studied mathematics and computer science at Harvey Mudd College, and is known for work on inner alignment, deceptive alignment, and alignment stress-testing.

Jacob Hilton is a researcher and executive director at Alignment Research Center, where he works on mechanistic approaches to outperforming random sampling. He previously worked at OpenAI on truthfulness, reinforcement learning, and interpretability for language models, earlier worked at Jane Street, completed a PhD in mathematics at the University of Leeds, and later coauthored Anthropic work on constitutional classifiers.

Sandipan Kundu is a member of technical staff at Anthropic. His public The Org profile says he previously held postdoctoral positions at Johns Hopkins and Cornell, worked and studied at the University of Texas at Austin, and earned a master's degree in physics from the Indian Institute of Technology Kanpur.

Sheer El-Showk is a member of technical staff at Anthropic. His public The Org profile says he is also CTO at Lore AI and founder of Nascent AI, previously worked as a senior software engineer at Coiled and held postdoctoral research fellowships at CERN and the CEA, and earned physics and mathematical physics degrees from UC Berkeley and the University of Amsterdam.

William Saunders is a research scientist at Anthropic working on aligning and evaluating language models. His public homepage says he works at the intersection of game theory, optimization, and deep learning, previously interned at OpenAI, DeepMind, and Mila, studied mathematics at the University of Oxford, and is a PhD student in machine learning at Carnegie Mellon University.

David Krueger is an assistant professor in robust, reasoning, and responsible AI at the University of Montreal and a core academic member at Mila. His homepage says he trained in deep learning under Yoshua Bengio, Roland Memisevic, and Aaron Courville from 2013 to 2021, was at the University of Cambridge from 2021 to 2024, and founded the nonprofit Evitable in 2025.

Jacob Steinhardt is an Associate Professor of Statistics and EECS at UC Berkeley and the founder and CEO of Transluce, a nonprofit research lab building technology to understand frontier AI systems. He previously spent a postdoctoral year at OpenAI and Open Philanthropy after completing his PhD at Stanford University with Percy Liang, and he coauthored Anthropic interpretability work such as Tracing the thoughts of a large language model.

Neel Nanda is an independent researcher focused on mechanistic interpretability and understanding neural networks. He previously worked on Anthropic's model diffing team, did the ML Alignment & Theory Scholars program, studied mathematics at the University of Cambridge, and is known for interpretability tooling such as TransformerLens.

Andy Zou is a final-year PhD student in the Language Technologies Institute at Carnegie Mellon University. His homepage says he studies large language models, reasoning, coding, and AI safety, and his CV shows previous internships at Scale AI and Google after BS and MS degrees in electrical engineering and computer sciences from UC Berkeley.

Carl Vondrick is an Assistant Professor of Computer Science at Columbia University and a researcher at Apple whose work spans computer vision, machine learning, and multimodal systems. He previously worked as a research scientist at Google and a visiting researcher at Cruise, completed his PhD at MIT in 2017 after a BS at UC Irvine, and coauthored Anthropic interpretability work such as Tracing the thoughts of a large language model.

Cem Anil is a research scientist at Anthropic and part of the company's Alignment Science team. His homepage says he recently completed a PhD at the University of Toronto and Vector Institute supervised by Roger Grosse and Geoffrey Hinton. He studies the intersection of deep learning and AI safety, especially robustness and generalization in large language models and scaling laws for dangerous capabilities.

Researcher at Anthropic whose public report authorships and scholarly profiles cover language model evaluation, AI safety, and robustness.

Founder and CEO of Ricursive Intelligence, a frontier AI lab targeting chip design; previously a Senior Staff Research Scientist at Google DeepMind and an early employee at Anthropic.

Ryan Greenblatt is chief scientist at Redwood Research. His public Redwood and Forethought profiles identify him as part of Redwood's AI safety team and say he holds a BS in applied mathematics and computer science from Brown University.

Max Tegmark is a physicist and professor at MIT whose work spans cosmology, fundamental physics, and the implications of advanced AI systems. After earning his PhD in physics from the University of California, Berkeley in 1994 and undergraduate training at the Royal Institute of Technology in Stockholm, he worked as a postdoctoral researcher at the University of Pennsylvania before joining MIT and later coauthored Anthropic interpretability work on large language models.

Research scientist at Anthropic whose public work includes AI alignment, reinforcement learning from human feedback, and model behavior.

Nelson Elhage is an engineer and researcher at Anthropic, where he works on the pretraining team after earlier work on reverse-engineering large language models. He previously worked at Stripe and Ksplice/Oracle on systems software and is known for open-source systems projects such as livegrep and reptyr.

Senior research engineer at Anthropic interested in agent foundations, model organisms of misalignment, and human-computer interaction.

Nikhil Prakash is a research scientist at Anthropic. His homepage says he recently completed a PhD in computer science at Berkeley advised by Jacob Steinhardt, after earlier work at Mila and Carnegie Mellon University. He studies learning in deep networks and the principles that lead to emergent phenomena.

Yanda Chen is a member of technical staff at Anthropic and a PhD candidate in computer science at Georgetown University advised by Kevin Knight. His homepage says he previously worked at Allen Institute for AI and focuses on AI safety, natural language processing, and deep learning.

Amanda Askell

Deep Ganguli

Tom Henighan

Aengus Lynch

Evan Hubinger

Jacob Hilton

Sandipan Kundu

Sheer El-Showk

William Saunders

David Krueger

Jacob Steinhardt

Neel Nanda

Andy Zou

Carl Vondrick

Cem Anil

Saurav Kadavath

Anna Goldie

Ryan Greenblatt

Max Tegmark

Liane Lovitt

Nelson Elhage

Samuel Marks

Nikhil Prakash

Yanda Chen