Prof. John Urschel

Professor Urschel's interests largely consist of topics in numerical linear algebra, spectral graph theory, and theoretical machine learning, most of which share a foundation in matrix analysis. Below is a brief description of each topic and my interests within each discipline.

Numerical Linear Algebra: The field of numerical linear algebra is fundamentally concerned with the efficient computation of approximate solutions to problems in mathematical analysis through matrix operations. Two common examples include the numerical solution of linear systems Ax = b and eigenvalue problems Ax = λx. Research is mostly focused on matrix factorizations and moment-based eigenvalue algorithms.