Department Directory

Andrea Stevenson Won directs the Virtual Embodiment Lab. The lab's research focuses on how mediated experiences change people’s perceptions, especially in immersive media. Research areas include the clinical applications of virtual reality, and how nonverbal behavior as rendered in virtual environments affects collaboration and teamwork. Andrea Stevenson Won completed her PhD in the Virtual Human Interaction Lab in the Department of Communication at Stanford University. She also holds an MS in Biomedical Visualization from the University of Illinois at Chicago.
 

Daniel Susser is an associate professor of information science. His research focuses on ethics, politics, and policy in computing. A philosopher by training, he studies governance problems raised by new and emerging data-driven technologies and the underlying conceptual and normative problems that make it difficult to understand and tackle them. He has broad interests in technology ethics and policy, philosophy of technology, and science and technology studies, especially critical questions about data, privacy, and the ethics of automation.

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.

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.

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).
 

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.
 

Qian Yang is an assistant professor of information science. She is a human-AI interaction designer and researcher. With her students, Yang designs novel AI applications and services that demonstrate new ways of bridging together frontier AI technologies, user needs, and societal betterment goals. For this work, she has received many academic and industry awards, including Schmidt Futures' Inaugural AI2050 Fellowship. She co-directs the Cornell Digital and AI Literacy Initiative with Natalie Bazarova. Yang is also a senior fellow at the Cornell Brooks School Tech Policy Institute.

Yian Yin is an assistant professor of information science. His research applies and develops novel computational tools to understand how individual, social, and environmental processes independently and jointly promote (or inhibit) scientific progress and innovation achievements. As a computational social scientist, he has also used science and innovation as a powerful lens to examine broader processes and outcomes in a wide range of complex social processes, from artistic and cultural productions to public policy, from media attention to market competition to human conflict. His research has been published in top general audience venues such as Science, Nature, and Nature Human Behaviour and featured in media outlets such as Forbes, Scientific American, The Atlantic, Harvard Business Review, and MIT Technology Review. In 2023, he was named to Forbes 30 under 30: Science list.

Ramin Zabih is a Professor at Cornell Tech and in the Computer Science Department at Cornell University. He received his undergraduate degrees from MIT in Computer Science and Math, and his Ph.D. from Stanford in Computer Science.

Cheng Zhang is an associate professor of information science. His research examines how to solicit information on and around the human body to address real-world challenges in various application areas, such as interaction, health sensing, and activity recognition. He usually builds novel sensing systems from the bottom to the top, including understanding the physical phenomenon, building hardware prototypes, designing form factors, processing data, and designing algorithms (machine learning or physics-based modeling).  

Malte Ziewitz studies the changing role of data-driven technologies in establishing, maintaining, and subverting social order. An ethnographer and STS scholar, his recent work looked at the lived experience of credit scoring subjects, the search engine optimization (SEO) industry, and attempts at algorithmic regulation. 
 

 
 

Dr. Kaitlyn Zhou is an incoming professor at Cornell University in the Bowers College of Computing and Information Science. Her contributions have been recognized at top-tier conferences in NLP and HCI. She has received awards such as NAACL Best Paper Runner-Up, MIT EECS Rising Star, Stanford Graduate Fellowship, and the College of Engineering Dean’s Medal and her methods have been featured in high-profile news outlets like the New York Times and Wall Street Journal. Kaitlyn received her PhD in Computer Science from Stanford University where she was advised by Dan Jurafsky. Kaitlyn has long advocated for increased access, inclusion, and equity in higher education and was appointed by the Washington State Governor to serve on the University of Washington Board of Regents.