Sandra Zilles is interested in methods for modelling and exploiting special types of interaction with machines to enable them to learn using less data than conventional approaches

Data efficient learning

Sandra Zilles and her team focus on theoretical aspects of machine learning. She is particularly interested in methods for modelling and exploiting special types of interaction with machines to enable them to learn using less data than conventional approaches. Intuitively, the research will make intelligent machines exploit the quality of well-chosen data rather than requiring a large quantity of potentially expensive data. The models and algorithmic techniques that will ultimately arise from this research may provide efficient solutions to complex problems in artificial intelligence – at a lower cost and with less data than is currently possible. Sandra and her team are currently working on the interplay between data-efficient teaching and avoiding collusion, on trust in multi-agent systems, on developing algorithms for aggregating the preferences of various entities in a system, and studying how to learn succinct representations of structured textual data (such as DNA sequences, bibliography entries, computer programs, etc.).

Sandra is a Canada CIFAR AI Chair at Amii, a Professor in the Department of Computer Science at the University of Regina and a Canada Research Chair in Computational Learning Theory. Sandra is an Associate Editor for IEEE Transactions on Pattern Analysis and Machine Intelligence, as well as the Journal of Computer and System Sciences. She has served on program committees for many international conferences including NeurIPS, IJCAI, COLT and AAAI, as well as co-chairing the conference steering committee for ALT. Sandra received a Membership in the College of New Scholars, Artists, and Scientists of the Royal Society of Canada (2017 - 2024), a national system of multidisciplinary recognition for the emerging generation of Canadian intellectual leadership. Sandra is proud to have supervised over 35 M.Sc. and Ph.D. students. She has published over 140 papers, which have been cited nearly 1200 times. In 2003, she received her Ph.D. in Computer Science at the University of Kaiserslautern, Germany.