Vazirani has made seminal contributions to several areas of the theory of algorithms and computational complexity; in particular, algorithmic matching theory, combinatorial optimization, approximation algorithms, and algorithmic game theory. He is one of the founders of algorithmic game theory, focusing on the computability of market equilibria. His current research is centered on matching-based market design.
Vazirani is a Guggenheim Fellow, an ACM Fellow and the recipient of the 2022 INFORMS John von Neumann Theory Prize. He is the author of the now-classic book, Approximation Algorithms. His co-edited books include Algorithmic Game Theory and Online and Matching-Based Market Design.
Ph.D., Computer Science, UC Berkeley