I am a professor at Cornell University. My research focuses on algorithms and networks, the roles they play in large-scale social and information systems, and their broader societal implications. My work has been supported by an NSF Career Award, an ONR Young Investigator Award, a MacArthur Foundation Fellowship, a Packard Foundation Fellowship, a Simons Investigator Award, a Sloan Foundation Fellowship, a Vannevar Bush Faculty Fellowship, and grants from Facebook, Google, Yahoo, the MacArthur and Simons Foundations, and the AFOSR, ARO, and NSF. I am a member of the National Academy of Sciences, the National Academy of Engineering, the American Academy of Arts and Sciences, and the American Philosophical Society.

Pamela Samuelson is the Richard M. Sherman Distinguished Professor of Law and Information at the University of California, Berkeley. She is recognized as a pioneer in digital copyright law, intellectual property, cyberlaw and information policy. Since 1996, she has held a joint appointment at Berkeley Law School and UC Berkeley’s School of Information. Samuelson is a director of the internationally-renowned Berkeley Center for Law & Technology. She is co-founder and chair of the board of Authors Alliance, a nonprofit organization that promotes the public interest in access to knowledge. She also serves on the board of directors of the Electronic Frontier Foundation, as well as on the advisory boards for the Electronic Privacy Information Center , the Center for Democracy & Technology, and Public Knowledge.

Professor Frauke Kreuter is Co-Director of the Social Data Science Center and faculty member in the Joint Program in Survey Methodology at the University of Maryland, USA; and Professor of Statistics and Data Science at the Ludwig-Maximilians-University of Munich. She is an elected fellow of the American Statistical Association and the 2020 recipient of the Warren Mitofsky Innovators Award of the American Association for Public Opinion Research. In addition to her academic work Dr. Kreuter is the Founder of the International Program for Survey and Data Science, developed in response to the increasing demand from researchers and practitioners for the appropriate methods and right tools to face a changing data environment; Co-Founder of the Coleridge Initiative, whose goal is to accelerate data-driven research and policy around human beings and their interactions for program management, policy development, and scholarly purposes by enabling efficient, effective, and secure access to sensitive data about society and the economy. coleridgeinitiative.org; and Co-Founder of the German language podcast Dig Deep.

I am an Associate Professor in the EECS Department at UC Berkeley, currently on leave to head AI Safety and Alignment at Google DeepMind.

The goal of my research at UC Berkeley has been to enable AI agents (from robots to cars to LLMs to recommender systems) to work with, around, and in support of people. I run the InterACT Lab, where we focus on algorithms for human-AI and human-robot interaction. One of the core problems we have worked on since the lab's inception is AI alignment: getting AI agents to do what people actually want -- this has meant learning reward functions interactively, from diverse human feedback forms, across different modalities, while maintaining uncertainty. We have also contributed to algorithms for human-AI collaboration and coordination, like agents fluently working together with human-driven avatars in games, assistance and adaption in brain-machine interfaces, and autonomous cars sharing the road with human drivers.

At Google DeepMind, I currently lead a collection of teams responsible both for safety of the current Gemini models, as well as preparing for Gemini capabilities to keep advancing and ensuring that safety advances hand-in-hand. This means ensuring Gemini models are and will be aligned with human goals and values, including avoiding present-day harms and catastrophic risks, enabling models to better and more robustly understand human preferences, enabling informed oversight, increasing robustness to adversarial attacks, and accounting for the plurality of human values and viewpoints.

Previously, I helped found and serve on the steering committee for the Berkeley AI Research (BAIR) Lab. I have been (and still am) a co-PI of the Center for Human-Compatible AI. I have consulted for Waymo for the past 6 years, helping with the roadmap for how to deploy an increasingly learning-based safety-critical system. I've been honored by the Sloan Fellowship, MIT TR35, the Okawa award, an NSF CAREER award, and the PECASE award. I take most pride in my former students, who have gone on to faculty positions at MIT, Stanford, CMU, and Princeton, and to industry positions at DeepMind, Waymo, and Meta.

Andreas Krause is a Professor of Computer Science at ETH Zurich, where he leads the Learning & Adaptive Systems Group, serves as Academic Co-Director of the Swiss Data Science Center, Chair of the ETH AI Center, and co-founded the ETH spin-off LatticeFlow AI. He is a Fellow at the Max Planck Institute for Intelligent Systems, ACM Fellow, IEEE Fellow, ELLIS Fellow and a Microsoft Research Faculty Fellow. He received the Rössler Prize, ERC Starting Investigator and Consolidator grants, the German Pattern Recognition Award, an NSF CAREER award, Test of Time awards at KDD 2019 and ICML 2020, as well as the ETH Golden Owl teaching award. Andreas Krause served as Program Co-Chair for ICML 2018 and General Chair for ICML 2023 and serves as Action Editor for the Journal of Machine Learning Research. From 2023-24, he served on the United Nations’ High-level Advisory Body on AI.