Michael J. Lindsey

Michael J. Lindsey is an Assistant Professor in the Department of Mathematics at the University of California, Berkeley, and a Faculty Scientist at Lawrence Berkeley National Laboratory. His research focuses on computational methods driven by Numerical Linear Algebra, Optimization, and Randomization, particularly for High-Dimensional Scientific Computing in quantum many-body problems and applied probability.

• University: UC Berkeley (Assistant Professor since 2022)
• Lab Affiliation: Mathematics Group at Lawrence Berkeley National Laboratory
• Email: lindsey@berkeley.edu

His work includes Semidefinite Relaxation for quantum and classical problems, Monte Carlo Sampling techniques, and Tensor Networks for high-dimensional functions. He has pioneered Variational Embedding theory with guaranteed energy bounds and scalable solvers for quantum systems.

Recent publications span Quantum Chemistry, Machine Learning, and High-Dimensional Probability, with applications to Electronic Structure, Molecular Dynamics, and Optimal Transport. He received the 2024 Hellman Fellowship and the 2019 SIAM Student Paper Prize.

Teaching includes graduate and undergraduate courses in numerical analysis and applied mathematics at UC Berkeley and New York University. He also organizes the HDSC Seminar on high-dimensional scientific computing.