Game theory, fair division, strategic collaborative behavior, and their applications in various domains. Also interested in algorithmic transparency, and ethics in AI/ML.
Yair Zick is currently working on a variety of topics at the intersection of game theory, fair division and AI. His core interests are in computational aspects of game theory and fair division. Currently, he works on the fair allocation of indivisible resources, with a particular focus on justice criteria such as envy-freeness, stability and diversity. He is also interested in making machine learning models more trustworthy, by ensuring that we can explain their decisions in a reasonable manner, while preserving other criteria such as fairness and privacy. Finally, he is interested in applying machine learning concepts to game theory, in particular in how learning-theoretic concepts can be applied to obtain data-driven solutions to problems in game theory and economics.
Zick is an assistant professor at the College of Information Systems and Computer Sciences, UMass Amherst. Prior to that, he was an assistant professor at the NUS School of Computing. He obtained his PhD (mathematics) from Nanyang Technological University, Singapore in 2014, and a BSc (mathematics, "Amirim" honors program) from the Hebrew University of Jerusalem.