Karthik Sridharan is an associate professor in the Department of Computer Science at Cornell University. Prior to that, he was a postdoctoral research associate at the University of Pennsylvania, jointly with Alexander Rakhlin and Michael Kearns. He obtained his Ph.D. from Toyota Technological Institute at Chicago where his thesis advisor was Nathan Srebro. His primary area of research is theoretical machine learning, with interests in statistical learning theory, online learning, optimization, empirical process theory, concentration inequalities, and game theory.

Noah Stephens-Davidowitz is an assistant professor in the Department of Computer Science, and a member of the applied math field and the mathematics field. His research to date has focused primarily on the study of lattices. He is also interested more broadly in theoretical computer science, cryptography, and geometry.

Jennifer J. Sun is an assistant professor in the Department of Computer Science at Cornell University. Her research develops AI for scientists to accelerate discovery across fields. Her group works with researchers and domain experts to build approaches that enable new ways to collaborate between human experts and machine learning systems. Her work intersects different areas of computer vision and machine learning, including representation learning, program synthesis, generative modeling, and human-AI collaboration. Sun received her Ph.D. in computing and mathematical science from the California Institute of Technology and her bachelor's degree in engineering science (electrical and computer engineering) from the University of Toronto.

Wen Sun is an assistant professor of computer science at Cornell Tech and the Cornell Ann S. Bowers College of Computing and Information Science. His research focuses on machine learning and artificial intelligence. Sun’s group at Cornell works on reinforcement learning and its applications to generative AI and robotics.

Éva Tardos is the Jacob Gould Schurman Professor of Computer Science. Her research interests include algorithms and algorithmic game theory, the subarea of theoretical computer science theory of designing and analyzing systems, and algorithms for selfish users. Her research focuses on algorithms and games on networks and simple auctions. She is most known for her work on quantifying the efficiency of selfish routing. Tardos received her Dipl.Math. and Ph.D. from Eötvös University, in Hungary. She has been elected to the National Academy of Engineering, the National Academy of Sciences, the American Philosophical Society, the American Academy of Arts and Sciences. She is the recipient of a number of fellowships and awards including the Packard Fellowship and the IEEE von Neumann Medal.

Tim Teitelbaum's early research focus was on Integrated Development Environments (IDEs), Syntax-Directed Editing, and Incremental Computation. His later work was on Automated Program Analysis for cybersecurity.

John Thickstun is an assistant professor of computer science. He works on machine learning and generative models. Thickstun is interested in methods that control the behavior of models, both from the perspective of a user who hopes to use a model to accomplish concrete tasks, and from the perspective of a model provider or policymaker who hopes to broadly regulate the outputs of a model. He is also interested in applications of generative models that push beyond the standard text and image modalities, including music technologies.