The Economics Department at Princeton University is delighted to welcome Fedor Sandormirskiy, formerly an Associate Research Scholar and Lecturer with the department, to the faculty as an Assistant Professor of Economics.

Sandomirskiy is a microeconomic theorist specializing in information economics and economic design. His research brings new methodological tools to understand interactions among strategic agents and improve the outcomes of these interactions by proposing new mechanisms. It blends microeconomic insights with ideas from algorithmic game theory and relies on the interplay of probability, convexity, and functional analysis. Sandomirskiy earned his Ph.D. in Mathematical Methods of Economics from the Central Economics and Mathematics Institute at the Russian Academy of Sciences in 2014. He also holds a MSc in Mathematical Physics from St.Petersburg State University.

Sandomirskiy’s special interests include:

• Information, privacy, and learning: Information economics studies how agents’ behavior is affected by the information they have access to. His key interest is methods for studying problems where different agents acquire information from different sources.
• Fairness and efficiency in economic design: normative & algorithmic tools: The classical theory of economic design suffers from impossibility results: mild normatively appealing conditions on a mechanism are often incompatible. His key interest is in methods of escaping these impossibilities.
• Common patterns behind his first two interests and beyond: Seemingly unrelated economic theory problems are connected to majorization, optimal transportation, maximal flows, mathematical tomography, and, more generally, measures with given marginals and their extreme points.

His research contributions in these areas include, “Feasible joint posterior beliefs,” published in the Journal of Political Economy, 2021, 129(9), which describes agents’ belief distributions that can emerge when there are multiple sources of information, “Competitive division of a mixed manna,” published in Econometrica, 2017, vol.85:6, p.1847-1871, which describes the pseudo-market approach for bads and mixed bads/goods problems, and “Private Private Information,” forthcoming in the Journal of Political Economy, which introduces a novel framework for understanding information privacy through the lens of mathematical tomography, a subfield of optimal transportation theory. Current research further develops the optimal transportation perspective, exploring its applications across various economic domains, such as market design, multi-agent information design, and auctions. More of Sandomirskiy’s research can be found on his website.

“Princeton has long existed in my mind as something between legend and textbook—a place that shaped modern research in so many fields and gave birth to game theory. I never dreamed I could become part of it,” Sandomirskiy said. “Dream or not, I’m excited to explore the fundamentals of how information and incentives affect strategic interactions and use these insights to design better economic mechanisms, contributing to the excellence of our amazing theory group and strengthening its connections with CS and math.”