My research is in machine learning theory and algorithms. I focus mainly on active and interactive learning: a setting where the data source and the algorithm interact in an attempt to improve learning accuracy while decreasing information costs. Much of my work revolves around developing general-purpose algorithms that can be useful in many different applications. I am also interested in fairness in machine learning. Please see my personal webpage for a list of my publications.
Open positions
I am hiring Computer Science Ph.D. and M.Sc. students for the Fall of 2024. I am looking for students with a strong mathematical background and an interest in machine learning theory. If you are interested, you are welcome to email me. Your email subject line should specify the research topic you are most interested in. In your email, please let me know why you are interested in being a part of my team. Please also attach your CV, transcripts and any other supporting material that you think might be relevant. Note that I will not follow links to external material, due to computer security reasons.
Block Heading
Sivan Sabato is an Associate Professor at the Department of Computing and Software at McMaster University, a Canada CIFAR AI Chair and a faculty member at the Vector Institute. Prior to that, she was at the Department of Computer Science at Ben-Gurion University, following a post-doctoral fellowship at Microsoft Research New England. She received her PhD from the School of Computer Science and Engineering at the Hebrew University of Jerusalem. Sivan serves as an Action Editor for the Journal of Machine Learning Research and for Transactions of Machine Learning Research, and routinely serves as an Area Chair at Machine Learning conferences such as NeurIPS, ICML, COLT, ALT and AISTATS. She was also the Publication Chair for ALT 2021 and a Publication Co-Chair for ICML 2022 and 2023.
