Department Directory

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.

Angelique Taylor is the Andrew H. and Ann R. Tisch Assistant Professor at Cornell Tech and the Cornell Ann S. Bowers College of Computing and Information Science.

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.

Immanuel Trummer is an associate professor of computer science. In his research, he makes data analysis more efficient and more user-friendly, often leveraging methods from the area of machine learning. His papers were selected for “Best of VLDB,” “Best of SIGMOD,” the ACM SIGMOD Research Highlight Award, and for publication in CACM as a CACM Research Highlight. He is a recipient of the NSF CAREER Award and multiple Google Faculty Research Awards. Trummer obtained a Ph.D. in computer science from the École Polytechnique Fédérale de Lausanne and a French-German double diploma in computer science and engineering.

Professor Emeritus; Computer Science; Ph.D., Univ of Michigan, 1973

Robbert van Renesse is a professor in the Department of Computer Science at Cornell University. He is a member of the Systems and Networking group and is interested in distributed systems, particularly in their  fault tolerance and scalability aspects. He is co-editor-in-chief for ACM Transactions on Computing Systems. He also plays jazz guitar and banjo in various bands, including the Ageless Jazz Band, the The JazzHappensBand, and Soda Ash Six. Van Renesse received his M.Sc. in mathematics and computer science and his Ph.D. in computer science, both from the Vrije Universiteit under the supervision of Andrew S. Tanenbaum. He is a Fellow of the Association of Computing Machinery.

Anke van Zuylen is a teaching professor in the Department of Computer Science. Her research interests are in combinatorial optimization. She designs and analyzes algorithms for optimization problems arising in areas such as: information science, in particular, aggregating inconsistent structured information; network design, scheduling and logistics, and computational biology.

Aditya Vashistha is an assistant professor in information science at Cornell Bowers, where he advises students in information science and computer science. He leads the Cornell Global AI Initiative – an interdisciplinary, university-wide effort to integrate global perspectives into the design, development, evaluation, and governance of AI technologies.

Fei Wang is an associate professor at Department of Population Health Sciences, Weill Cornell Medicine, Cornell University. His major researchinterest is data mining, machine learning and their applications in health data science. He has published on the top venues of related areas such as ICML, KDD, NeurIPS, AAAI, JAMA Internal Medicine, Annals of Internal Medicine, etc. His team won the championship of the NIPS/Kaggle Challenge on Classification of Clinically Actionable Genetic Mutations in 2017 and Parkinson’s Progression Markers Initiative data challenge organized by Michael J. Fox Foundation in 2016. Dr. Wang is the recipient of the NSF CAREER Award in 2018, the inaugural research leadership award in IEEE International Conference on Health Informatics (ICHI) 2019, Amazon Machine Learning for Research Award in 2017 and 2019, Google Faculty Research Award in 2020, Sanofi iDEA Award in 2021. Dr. Wang was the chair of the Knowledge Discovery and Data Miningworking group in American Medical Informatics Association (AMIA) in 2018-2019. Dr. Wang’s research has been supported by funding agencies including NSF, NIH, ONR, PCORI and MJFF. Dr. Wang is a Fellow of the American Medical Informatics Association (AMIA), a Fellow of the International Academy of Health Sciences and Informatics (IAHSI), and a Distinguished Member of the Association for Computing Machinery (ACM).
 

Hakim Weatherspoon is a professor in the Department of Computer Science. His research interests cover various aspects of information systems, distributed systems, network systems, and peer-to-peer systems. In these areas, he particularly focuses on fault-tolerance, reliability, security, and performance of internet-scale systems with decentralized – autonomous, federated, multi-organizational, and cooperative – control. 

Kilian Weinberger is a professor in the Department of Computer Science at Cornell University. He received his Ph.D. from the University of Pennsylvania in machine learning under the supervision of Lawrence Saul, and his undergraduate degree in mathematics and computing from the University of Oxford. In 2011 he was awarded the Outstanding AAAI Senior Program Chair Award and in 2012 he received an NSF CAREER award. He is the recipient of the Daniel M. Lazar '29 Excellence in Teaching Award (2016) and the Ann S. Bowers Teaching and Advising Excellence Award (2024). As of 2024, he is an ACM and AAAI fellow and in 2021 became a Blavatnik National Awards Finalist. Since 2024 he has been a member of the Sloan Research Fellowships Selection Committee. Weinberger's research focuses on machine learning and its applications. In particular, he has worked on learning under resource constraints, metric learning, AI in science, computer vision, autonomous vehicles, Gaussian processes, and deep learning. Before joining Cornell University, he was an associate professor at Washington University in St. Louis, and before that, he worked as a research scientist at Yahoo! Research in Santa Clara. 

Walker White is a senior lecturer of computer science and a Stephen H. Weiss Provost's Teaching Fellow. A mathematical logician by training, White studied computable model theory for his thesis work, and then moved onto the design of high-level languages for databases and information systems. More recently, White has combined his professional research in databases and query languages with his hobbies in gaming and game design. He is the director of the Game Design Initiative at Cornell, which he helped launch in 2001 as one of the first official computer game programs of its kind and the first such program established at an Ivy League university. In his role as director, he leads Cornell’s undergraduate minor in game design. He received a Ph.D. in mathematics and a master’s in computer science from Cornell, and a bachelor’s in mathematics from Dartmouth.