Directory

Steve Jackson is a professor of information science and science & technology studies, with additional graduate field appointments in communication and public affairs. He is also the former chair of information science and former dean of William Keeton House. Since July 2023, he has also served as Vice Provost for Academic Innovation at Cornell.  

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. 

Wendy Ju is a professor of information science at Cornell Tech, the Cornell Ann S. Bowers College of Computing and Information Science, the Jacobs Technion-Cornell Institute, and the Technion-Israel Institute of Technology.

Ari Juels is the Weill Family Foundation and Joan and Sanford I. Weill Professor of computer science at Cornell Tech, the Cornell Ann S. Bowers College of Computing and Information Science, and the Jacobs Technion-Cornell Institute. He is co-director of the Initiative for CryptoCurrencies and Contracts (IC3). He is also the chief scientist at Chainlink Labs.

Malte Jung is an associate professor of information science at Cornell University and the Nancy H. ’62 and Philip M. ’62 Young Sesquicentennial Faculty Fellow. He directs the Interplay Research Studio that explores the interplay between people and automation.

Saleh Kalantari is the Lois and Mel Tukman Assistant Professor in Cornell University's Department of Human Centered Design, with graduate field faculty appointments in the Department of Information Science. He is the director of the Design and Augmented Intelligence Lab (DAIL) at Cornell, where his research group investigates human-technology partnerships in the design process with the goal of amplifying the effectiveness of design practice and expanding our knowledge about the outcomes of design. Dr. Kalantari's work promotes the generative-design approach and the adoption of new design technologies to improve the relationship between people and their created environments. Drawing from behavioral and neurological research methods, he studies human spatial experiences in both virtual and real-world contexts.
 

Kallus's research revolves around data-driven decision making in operations, the interplay of optimization and statistics in decision making and inference, and the analytical capacities and challenges of unstructured, large-scale, and web-based data. His works span basic theory, effective methodology, and novel applications and has been recognized by awards.
 

Cindy Hsin-Liu Kao is an Assistant Professor of Design + Environmental Analysis at Cornell University. She holds a Ph.D. from the MIT Media Lab. Her research practice themed Hybrid Body Craft blends aesthetic and cultural perspectives into the design of on-body interfaces. She also creates novel processes for crafting technology close to the body. Her research has been presented at various conferences and magazines (ACM CHI, UbiComp/ISWC, TEI, UIST, ACM Interactions, IEEE Pervasive Computing), while receiving media coverage by CNN, TIME, Forbes, Fast Company, WIRED, among others. Her work has been exhibited and shown internationally at The Boston Museum of Fine Art, Ars Electronica, Dutch Design Week, New York Fashion Week, and more. She has worked at Microsoft Research developing cosmetics-inspired wearables, and is a recipient of the Google Anita Borg Scholarship. Among her awards include an Honorable Mention/Best Paper Award at ACM CHI, UIST and ISWC, the A'Design Award, the Fast Company Innovation by Design Award Finalist, an Ars Electronica STARTS Prize Nomination, and the SXSW Interactive Innovation Award.
 

M. Elizabeth Karns is a lawyer and epidemiologist. Her teaching is directly connected to her practice, which has focused on statistical evidence, occupational illnesses, assault and harassment injuries, and reproductive harms. Her current work on data science ethics brings together professional practice norms, individual values, and organizational goals. 

Kengo Kato is a professor of statistics and data science. His research fields are mathematical statistics, econometrics, and economic statistics with a focus on high dimensional statistical and econometric models. In 2020, Kato was awarded the Japan Academy Medal, regarded as the most prestigious award for young Japanese researchers. Among his many awards and honors, he is also a fellow of the Institute of Mathematical Statistics (IMS) and the recipient of the Analysis Award from the Mathematical Society of Japan (2021). He is the editor-in-chief of Bernoulli and the associate editor of the Japanese Economic Review and the Journal of Statistical Planning and Inference.

Jaehee Kim's research interests are in the general fields of population-genetic dynamical systems, statistical genetics, and mathematical phylogenetics. She also applies mechanistic understanding of population genetics and evolutionary biology to solve important questions in mathematical epidemiology and forensic genetics.

Michael Kim is an assistant professor of computer science. His research investigates foundational questions about responsible machine learning. Much of this work aims to identify problematic behaviors that emerge in machine-learned models and to develop algorithmic tools that provably mitigate such behaviors. More broadly, he is interested in how the theory of computation can provide insight into emerging societal and scientific challenges.

Rene Kizilcec is an associate professor of information science at Cornell, where he directs the Cornell Future of Learning Lab. Kizilcec studies behavioral, psychological, and computational aspects of technology in education to inform practices and policies that promote learning, equity, and academic and career success. His work has appeared in Science and the Proceedings of the National Academy of Sciences, won multiple awards, and is funded by the National Science Foundation, Schmidt Futures Foundation, and Jacobs Foundation. Kizilcec holds a Ph.D. in communication and M.Sc. in statistics from Stanford University.

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.

Robert Kleinberg is a professor of computer science at Cornell University and a member of the field of information science. His research studies the design and analysis of algorithms and their applications to electronic commerce, networking, information retrieval, and other areas. Prior to receiving his doctorate from the Massachusetts Institute of Technology in 2005, Kleinberg spent three years at Akamai Technologies, where he assisted in designing the world's largest Internet Content Delivery Network. He is the recipient of a Microsoft Research New Faculty Fellowship, an Alfred P. Sloan Foundation Fellowship, and an NSF CAREER Award.
 
 

Allison Koenecke is an assistant professor of information science at Cornell Tech and the Cornell Ann S. Bowers College of Computing and Information Science. Her research on algorithmic fairness applies computational methods, such as machine learning and causal inference, to study societal inequities in domains from online services to public health.

Dan Kowal is an associate professor of statistics and data science. His research primarily revolves around three themes: (1) Bayesian models and algorithms for large and dependent (e.g., time series, spatial, functional) data, (2) modeling, generation, and imputation of mixed data, and (3) predictive inference for actionable and interpretable uncertainty quantification. He directs his research toward open questions in public health, epidemiology, physical activity data, economics, and finance. Recently, he has worked on addressing urgent issues related to racial inequities and biases in statistical modeling.

Dexter Kozen is the Joseph Newton Pew, Jr. Professor of Engineering Emeritus in the Department of Computer Science. His research interests span topics on the boundary of computer science and mathematics: design and analysis of algorithms, computational complexity theory, complexity of decision problems in logic and algebra, and logics and semantics of programming languages. He is the author of more than 200 research articles and four books. Kozen is a former Guggenheim fellow and a fellow of the Association of Computing Machinery, the American Association for the Advancement of Science, and the European Association of Theoretical Computer Science. He is a recipient of the John G. Kemeny Prize in Computing, an IBM Outstanding Innovation Award, the EATCS Award, the IEEE W. Wallace McDowell Award, and the ACM Alonzo Church Award.