Kent Quanrud is an Assistant Professor of Computer Science at Purdue University. He received his Ph.D. from the University of Illinois at Urbana-Champaign in 2019, where he was advised by Chandra Chekuri and Sariel Har-Peled. He was born in Japan and grew up in California. His research interests include approximation algorithms, randomized algorithms, combinatorial optimization, continuous optimization, online learning, and computational geometry. He is particularly interested in extremely scalable algorithms for fundamental problems in optimization.