James R. Lee

James R. Lee is a Professor in the Department of Computer Science at the University of Washington. His research spans theoretical computer science, probability, and geometry. He has held visiting scientist roles at Microsoft Research (2023, 2018, 2017) and participated in programs at the Simons Institute (2023, 2020, 2018, 2017, 2014).

• Research Interests: Algorithms, complexity theory, convex optimization, metric embeddings, spectral graph theory, probability, stochastic processes, and the interplay between discrete and continuous analysis.
• Teaching: Courses on modern algorithms, quantum computing, optimization theory, and spectral methods in theoretical computer science.

Scientific Contributions:

• Developed sparsification algorithms for generalized linear models and norms with near-linear size guarantees (STOC'24, FOCS'23).
• Extended Cheeger-type inequalities to higher eigenvalues (STOC'12, STOC'18).
• Proved super-polynomial lower bounds for LP/SDP relaxations in constraint satisfaction (STOC'15, FOCS'13).
• Disproved Benjamini-Papasoglou conjectures on annular separators (Discrete Comp. Geom. 2024).
• Advanced understanding of random walks in geometric and unimodular graphs (Israel J. Math. 2023, GAFA 2023).

Scientific Awards:

• Best Paper Award, STOC 2015