Research Expertise and Interest
applied mathematics, mathematical analysis, probability, numerical analysis, optimization, Monte Carlo methods
Michael Lindsey is an assistant professor in the Department of Mathematics. He works on computational methods driven by numerical linear algebra, optimization, and randomization, with a special focus on high-dimensional scientific computing problems. These include quantum many-body problems arising in quantum chemistry and condensed matter physics, as well as various problems in applied probability. Approaches draw on a wide variety of techniques including semidefinite relaxation, Monte Carlo sampling, and optimization over parametric function classes such as tensor networks and neural networks.