Directory

Kavita Bala is the 17th provost of Cornell University and professor of computer science. Previously, she served as the inaugural dean of the Cornell Ann S. Bowers College of Computing and Information Science and chair of the Department of Computer Science. In her research, she specializes in computer vision and computer graphics, leading research in visual recognition and search; and material modeling and perception. She co-founded GrokStyle, a visual recognition AI company that drew IKEA as a client, and was acquired by Facebook in 2019. Bala is a Fellow of the American Academy of Arts & Sciences (2025), an Association for Computing Machinery (ACM) Fellow (2019), Fellow of the SIGGRAPH Academy (2020), and recipient of the Computer Graphics Achievement Award (2020).

Tapomayukh "Tapo" Bhattacharjee is an assistant professor in the Department of Computer Science at Cornell University where he directs the EmPRISE Lab. He completed his Ph.D. in robotics from Georgia Institute of Technology and was an NIH Ruth L. Kirschstein NRSA postdoctoral research associate in Computer Science and Engineering at the University of Washington. He wants to enable robots to assist people with mobility limitations with activities of daily living. His work spans the fields of human-robot interaction, haptic perception, and robot manipulation and focuses on addressing the fundamental research question of how to leverage robot-world physical interactions in unstructured human environments to perform relevant activities of daily living. 

Jelena Bradic is a professor of statistics and data science. Bradic’s research centers on causal inference, machine learning, and high-dimensional robust statistics, with applications in areas including public health and policy learning. Before joining Cornell, she held positions at the University of California, San Diego, in both the Department of Mathematics and the Halıcıoğlu Data Science Institute. She received her Ph.D. in operations research and financial engineering, from Princeton University.

Diana Cai, is an assistant professor of computer science, beginning fall 2026. In her research, Cai designs and analyzes probabilistic machine learning methods for scientific discovery. She is motivated by real-world scientific constraints and develops methods in close collaboration with scientists across domains, including biology, chemistry, and physics. Previously, Cai was a research fellow in the Center for Computational Mathematics at the Flatiron Institute. She completed her M.A. and Ph.D. in computer science from Princeton University, and received an M.S. in statistics from the University of Chicago, and an A.B. in computer science and statistics from Harvard University.  Her work has been recognized by a Google Ph.D. Fellowship in Machine Learning, Rising Stars in EECS, a Rising Stars in Machine Learning Award from the University of Maryland, a School of Engineering and Applied Science Award for Excellence from Princeton University, and spotlight paper awards at the NeurIPS and ICML conferences.

Preston Culbertson draws on machine learning, computer vision, and control theory to develop robots that move like humans. Prior to joining Cornell, he was a research scientist at The AI Institute in Cambridge, Mass. He received his Ph.D. in mechanical engineering from Stanford University.

Cristian Danescu-Niculescu-Mizil is a professor of information science. His research aims at developing computational frameworks that can lead to a better understanding of human social behavior by unlocking the unprecedented potential of the large amounts of natural language data generated online. His awards and honors include a National Science Foundation CAREER Award, Google Research Faculty Award, and numerous Best Paper awards. His work has been featured in popular media outlets such as the New Scientist, NBC's The Today Show, NPR, BBC, WIRED, the New York Times, Wall Street Journal, and Washington Post. For publications, recent updates and more fun stuff, check out Cristian's webpage.

Christopher De Sa is an associate professor of computer science and a member of the Cornell Machine Learning Group where he leads the Relax ML Lab. His research interests include algorithmic, software, and hardware techniques for high-performance machine learning, with a focus on relaxed-consistency variants of stochastic algorithms such as asynchronous and low-precision stochastic gradient descent (SGD) and Markov chain Monte Carlo. His work builds towards using these techniques to construct data analytics and machine learning frameworks, including for deep learning, that are efficient, parallel, and distributed. De Sa received his B.S., M.A., and Ph.D. from Stanford University in electrical engineering.

Sarah Dean is an assistant professor of computer science. She studies the interplay between optimization, machine learning, and dynamics in real-world systems. Her research focuses on understanding the fundamentals of data-driven methods for control and decision-making, inspired by applications ranging from robotics to recommendation systems. She completed her postdoctoral research at the University of Washington and earned her M.S. and Ph.D. in electrical engineering and computer science at the University of California, Berkeley. Dean received her B.S.E. in electrical engineering and mathematics from the University of Pennsylvania. 

Kevin Ellis is an assistant professor of computer science. He works on program synthesis and neurosymbolic AI. Ellis earned his Ph.D. in cognitive science and his B.S. in physics with a concentration in linguistics from the Massachusetts Institute of Technology.

Kuan Fang is an assistant professor of computer science who conducts research at the intersection of robotics, machine learning, and computer vision. His research aims to enable robots to perform diverse and complex tasks in unstructured environments using deep learning. To achieve this, his lab develops scalable algorithms and systems for robot perception and control with the following focuses: acquiring versatile and generalizable skills for visuomotor control by learning from massive and diverse data; continuously improving the capabilities of robots through autonomous data collection and generation; and boosting generalization to novel tasks, environments, and robots by integrating prior knowledge from broad sources. Fang did his postdoctoral research at the University of California, Berkeley and received his Ph.D. and M.S. from Stanford University. His bachelor's degree is from Tsinghua University. Fang also spent time at the RAI Institute, Google Brain, Google X Robotics, and Microsoft Research Asia. 

Sainyam Galhotra is an assistant professor in computer science. Before that, he was a Computing Innovation Fellow pursuing postdoctoral research at the University of Chicago. The goal of his research is to develop data science tools for effective and responsible analytics.

Jiawei Ge will join Cornell University as an assistant professor of statistics and data science in summer 2027. Her research lies at the intersection of statistics, machine learning, and artificial intelligence. She develops principled and computationally efficient methods for learning from large, heterogeneous, and structured data, with the broader goal of building reliable and trustworthy AI systems. Her work spans the statistical foundations of large language models, network modeling, mixture modeling, and uncertainty quantification. She is also interested in interdisciplinary collaborations that integrate modern statistical methods with domain knowledge in biology, finance, and the social sciences. Her research has received recognition from leading journals in statistics and econometrics, including The Annals of Statistics and the Journal of Econometrics, and has appeared at premier machine learning venues, including NeurIPS, ICML, and ICLR. Ge is currently a postdoctoral researcher in the Department of Statistics at the University of California, Berkeley. She earned a Ph.D. in operations research and financial engineering from Princeton University and a bachelor’s degree in applied mathematics from Fudan University.

Carla Gomes is the Ronald C. and Antonia V. Nielsen Professor of Computing and Information Science, director of the Institute for Computational Sustainability at Cornell University, and co-director of the Cornell University AI for Science Institute. Gomes received a Ph.D. in computer science in artificial intelligence from the University of Edinburgh. Her research area is AI with a focus on large-scale constraint reasoning, optimization, and machine learning. 

In Memoriam: Joe Halpern, ‘towering’ computer scientist and mentor, dies at 72

Bharath Hariharan is an associate professor in computer science. He works on computer vision and machine learning, specifically, on important problems that defy the "Big Data" label. He enjoys problems that require marrying advances in machine learning with insights from computer vision, geometry, and domain-specific knowledge. A few of the research problems his group works on include recognition for satellite images and earth science and 4D reconstruction and recognition. An exhaustive list of publications is available on Google scholar. His work has been recognized with an NSF CAREER award and a PAMI Young Researcher Award. 

Haym Hirsh is a professor in the Department of Computer Science at Cornell University. His research has focused on foundations and applications of machine learning, data mining, information retrieval, and artificial intelligence, especially targeting questions that integrally involve both people and computing. Most recently these interests have turned to crowdsourcing, human computation, and collective intelligence. Haym received his B.S. from the Mathematics and Computer Science Departments at the University of California, Los Angeles, and his M.S. and Ph.D. from the Computer Science Department at Stanford University. Prior to moving to Cornell in 2013 to serve as dean of the Faculty of Computing and Information Science, Hirsh spent 24 years on the computer science faculty at Rutgers University, and has had visiting positions at AT&T Labs, Bar-Ilan University, Carnegie Mellon University, MIT, and the University of Zurich. From 2006-2010 he served as director of the Division of Information and Intelligent Systems at the National Science Foundation. In 2022 he was elected a Fellow of the American Association for the Advancement of Science. 
 

Nori Jacoby is an assistant professor in the Department of Psychology at Cornell University. His research focuses on the internal representations that support and shape our sensory and cognitive abilities, and on how those representations are themselves determined by both nature and nurture. He addresses these classic issues with new tools, both by applying machine learning techniques to behavioral experiments, and by expanding the scale and scope of experimental research via massive online experiments and fieldwork in locations around the globe. Nori completed his Ph.D. at the Edmond and Lily Safra Center for Brain Sciences (ELSC) at the Hebrew University of Jerusalem under the supervision of Naftali Tishby and Merav Ahissar, followed by postdoctoral positions at Josh McDermott's Computational Audition Lab at MIT, at Tom Griffiths's Computational Cognitive Science Lab at UC Berkeley, and as a Presidential Scholar in Society and Neuroscience at Columbia University. Before coming to Cornell Nori was a Research Group Leader at the Max Planck Institute for Empirical Aesthetics in Frankfurt.

Thorsten Joachims is the Jacob Gould Schurman Professor of computer science and information science at Cornell University. He is also the Vice Provost for Artificial Intelligence Strategy at Cornell, where he leads the Cornell AI Initiative and the AI Radical Collaboration. He previously served as the interim dean for Cornell Bowers, as associate dean for research for Cornell Bowers, and as chair of the Department of Information Science. He has also served as program chair of the ICML, KDD, and RecSys conferences, and he is a member of the IMLS Board and the SIGKDD Executive Committee. Thorsten Joachims joined Cornell in 2001 after finishing his Ph. D. as a student of Prof. Morik at the University of Dortmund, from where he also received a Diplom in computer science in 1997.

Jon Kleinberg is a professor in both computer science and information science. His research focuses on issues at the interface of networks and information, with an emphasis on the social and information networks that underpin the Web and other online media. His work has been supported by an NSF Career Award, an ONR Young Investigator Award, a MacArthur Foundation Fellowship, a Packard Foundation Fellowship, a Sloan Foundation Fellowship, and grants from Google, Yahoo!, and the NSF. He is 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.