The Ross & Muriel Cheriton Faculty Fellowship supports the work of a full-time faculty member in the David R. Cheriton School of Computer Science whose research is in the general areas of computer systems and computer networking.
The title of Faculty Fellow recognizes a faculty member whose scholarly work is widely known and respected internationally, who is an accomplished teacher at all levels, and who has displayed a high level of commitment and dedication to her or his department or school, the Faculty of Mathematics, and the University.
Current Ross & Muriel Cheriton Faculty Fellow
Professor Shai Ben-David's research interests span a spectrum of topics in the foundations of computer science and its applications, with a particular emphasis on statistical and computational machine learning.
The common thread throughout his research is the quest for mathematical foundations of real-world problems. In recent years much of his research has been directed towards providing mathematical analysis for popular machine-learning and data-mining paradigms that seem to lack solid theoretical justification.
Shai has looked into the performance guarantees one can provide for Support Vector Machines (with pessimistic conclusions), at Semi-Supervised Learning (once again, coming up with some inherent limitations of that approach), at the problem of domain adaptation paradigm (providing the first theoretical justifications to common practices), change detection in streaming data, at the Stability method for determining the number of clusters in a data set, and quite a few more topics.
Clustering is a wide research area, with many practical applications that also suffer from a lack of mathematical foundations. He has been working extensively to address the challenge of developing a theory that provides guidelines for choosing an appropriate clustering technique for a given task.
Previous Ross & Muriel Cheriton Faculty Fellows
|Ross & Muriel Cheriton Faculty Fellow||Year|