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.

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 an associate 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.

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. 
 

Thorsten Joachims is the Jacob Gould Schurman Professor of computer science and information science at Cornell University. He has also served as the interim dean for Cornell Bowers and as associate dean for research and as chair of the Department of Information Science. He is the director of the Cornell AI Initiative and Radical Collaboration. He has 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.

Sorin Lerner is the dean of the Cornell Ann S. Bowers College of Computing and Information Science, appointed Nov. 1, 2025. A professor of computer science, his research focuses on providing programmers with tools to make software more secure and reliable. 

David S. Matteson is a professor of statistics and data science at Cornell University and director of the National Institute of Statistical Sciences. He is also director of graduate studies in data science, and founding executive committee member for the Cornell Center for Data Science for Enterprise and Society. His research centers on statistical methods for modeling complex human and natural processes and systems, with expertise in dynamic, spatial, functional, and network data science and machine learning. He received a CAREER Award from the National Science Foundation, the Chancellor’s Award for Scholarship and Creative Activities from the State University of New York, the inaugural Ann S. Bowers Research Excellence Award, Faculty Research Awards from the Xerox/PARC Foundation and LinkedIn, and is a Fellow of the American Statistical Association (ASA) and Institute of Mathematical Statistics (IMS). He has served as lead PI and director for several National Science Foundation-funded collaborative institutes, and he founded and serves as editor-in-chief for the new open access ASA journal Data Science in Science.

Kristina Monakhova is an assistant professor in the Department of Computer Science at Cornell. She works on co-designing optics and algorithms to create better, smaller, and more capable cameras and microscopes.