Dr. Sivan Sabato

Associate Professor

Department of Computing and Software, McMaster University

Canada CIFAR AI Chair, Vector Institute

sabatos [at] mcmaster [dot] ca

Overview

I am an Associate Professor at the Department of Computing and Software at McMaster University. I am also a Canada CIFAR AI Chair and a Faculty Member at the Vector Institute of Artificial Intelligence. I hold an Associate Professor position at the Department of Computer Science at Ben-Gurion University of the Negev, where I am on an extended leave of absence.

I was a post-doctoral fellow at Microsoft Research New England. I received my Ph.D. from the School of Computer Science and Engineering at the Hebrew University of Jerusalem. I am a recipient of the Alon Scholarship of the Council for Higher Education of Israel for excellent new faculty. I am also a recipient of the Google Anita Borg Memorial Scholarship, and an alumna of the Adams Fellowship Program of the Israel Academy of Sciences and Humanities.

I serve as an Action Editor for the Journal of Machine Learning Research and for the Transactions of Machine Learning Research, and routinely serve as an Area Chair at Machine Learning conferences such as NeurIPS, ICML, COLT, ALT and AISTATS. I was also the Publication Chair for ALT 2021, and a Publication co-Chair for ICML 2022 and ICML 2023.

Machine Learning Research

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. The list of my publications is here. Code for published methods is available here.

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.