Directory

Bruce Turnbull received the B.S. from Cambridge University in 1967 and the Ph.D. from Cornell University in 1971. After serving on the faculty at Stanford University and at the University of Oxford, he joined Cornell University in 1976, where he is currently Professor in the School of Operations Research and Information Engineering where he previously served as Acting Director.

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.

Paul Velleman is a Professor Emeritus with Social Statistics in the Industrial and Labor Relations School. His research is focused on Distance and Online Learning, Healthcare, abd Statistical Theory, Methods and Analysis. He also does work with Data Analysis, Computer Applications, and Computer Graphics.
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Gili Vidan is an assistant professor in information science and a graduate field member in the Department of Science and Technology Studies and the Media Studies graduate minor field. Trained as a historian of computing, her work examines how shifts in abstract political notions such as trust and good governance are made concrete and transformed through the digital technologies we develop and use. In particular, Vidan focuses on the overlapping ways political, social, commercial, and epistemic values literally materialize in our payment and communication technologies, from automated check-processing to digital watermarking. Her book, “Technologies of Trust,” traces technical attempts to solve the problems of trust and authentication in the postwar U.S and has been accepted by the Infrastructures series at MIT Press.

Angelina Wang is an assistant professor of information science at Cornell Tech and the Cornell Ann S. Bowers College of Computing and Information Science. Her research is in the area of responsible AI.

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).
 

Y. Samuel (Sam) Wang is an assistant professor of statistics and data science. Prior to joining Cornell in 2021, he was a post-doc at the University of Chicago’s Booth School of Business, and he completed his Ph.D. in statistics at the University of Washington. He also previously worked as a management consultant before his Ph.D. studies. His primary research areas are graphical models and causal discovery.

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. 

Marten Wegkamp is a professor of statistics and data science. His research areas are mathematical statistics, empirical process theory, high-dimensional statistics, and statistical learning theory. He received a Ph.D. in mathematics from Leiden University in 1996 and joined the Cornell faculty in 2011.

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. 

Martin T. Wells, Ph.D., joined the Cornell faculty in 1987 and is the Charles A. Alexander Professor of Statistical Sciences. He is also a professor of social statistics, professor of biostatistics and epidemiology at Weill Medical School, and an elected member of the Cornell Law School faculty.

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.

Matthew Wilkens is an associate professor of information science. He uses quantitative and computational methods to study large-scale developments in literary and cultural history. His work has focused in particular on literary text mining, geolocation extraction, genre detection, and the cross-pollination of critical and social scientific methods. He also seeks to develop and apply natural language processing and artificial intelligence methods to large-scale datasets in domains including medicine, public health, economics, and the law.

David Williamson was born in Madison, Wisconsin, but grew up in the suburbs of Honolulu, Hawaii. He received his Ph.D. in 1993 from the Massachusetts Institute of Technology.  In 1995 he joined IBM Research, and from 2000-2003 was the Senior Manager of the Computer Science Principles and Methodologies Department at IBM's Almaden Research Center.  In 2004, he joined Cornell University as a professor in the School of Operations Research and Information Engineering, and the Faculty of Computing and Information Science.

Dr. Williamson is well-known for his work on the topic of approximation algorithms, and is a coauthor of the book "The Design of Approximation Algorithms", published by Cambridge University Press. His Ph.D. dissertation on designing low-cost survivable networks was awarded several prizes, including the 1996 SIAM DiPrima Prize and the 1994 Tucker Prize from the Mathematical Programming Society. His work with Michel Goemans on the uses of semidefinite programming in approximation algorithms was awarded the 1999 SIAM Activity Group on Optimization prize, and the 2000 Fulkerson Prize from the Mathematical Programming Society and the American Mathematical Society. He is the editor-in-chief for the SIAM Journal on Discrete Mathematics, and has served as an associate editor on several other journals, including Mathematics of Operations Research and the SIAM Journal on Computing.