Sandra Zilles 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.
Zilles and her research team focus on theoretical aspects of machine learning. She 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. She is working on several challenges: the interplay between data-efficient teaching and avoiding collusion; on trust in multi-agent systems; developing algorithms for aggregating the preferences of various entities in a system; and, learning succinct representations of structured textual data (such as DNA sequences, bibliography entries, and computer programs).
- Membership in the College of New Scholars, Artists, and Scientists of the Royal Society of Canada, 2017 - 2024
- NSERC Canada Research Chair (Tier 2) in Computational Learning Theory, 2010 - 2017 and 2017 - 2022
- CACS/AIC (Canadian Association for Computer Science) Outstanding Young Researcher Award, 2013
Alanazi, E., Mouhoub, M., & Zilles, S. (2020). The complexity of exact learning of acyclic conditional preference networks from swap examples. Artificial Intelligence, 278, 103182.
Gao, Z., Ries, C., Simon, H. U., & Zilles, S. (2017). Preference-based teaching. The Journal of Machine Learning Research, 18(1), 1012-1043.
Doliwa, T., Fan, G., Simon, H. U., & Zilles, S. (2014). Recursive teaching dimension, VC-dimension and sample compression. The Journal of Machine Learning Research, 15(1), 3107-3131.
Zilles, S., Lange, S., Holte, R., Zinkevich, M., & Cesa-Bianchi, N. (2011). Models of cooperative teaching and learning. Journal of Machine Learning Research, 12(2).
Arfaee, S. J., Zilles, S., & Holte, R. C. (2011). Learning heuristic functions for large state spaces. Artificial Intelligence, 175(16-17), 2075-2098.
CIFAR is a registered charitable organization supported by the governments of Canada and Quebec, as well as foundations, individuals, corporations and Canadian and international partner organizations.