John Wilmes
Assistant Professor of Mathematics

Degrees
University of Chicago, Ph.D.University of Chicago, M.S.
Reed College, B.A.
Expertise
Combinatorics. Algorithms. Machine Learning.Profile
My research is in the theory of computing and combinatorics. A major area of focus is at theintersection of the algorithmic Graph Isomorphism problem and algebraic combinatorics. The analysis
of graph isomorphism algorithms is often closely related to the complexity of the automorphism
group, and I am therefore particularly interested in the connection between structure and symmetry
of graphs. Another primary area of interest is in computational learning theory, particularly in
provable guarantees for neural network algorithms.
Courses Taught
MATH | 15a | Applied Linear Algebra |
MATH | 16b | Applied Linear Algebra Practicum |
MATH | 122a | Numerical Methods and Big Data |
MATH | 124a | Optimization |
Scholarship
Santosh Vempala and John Wilmes. Gradient Descent for One-Hidden-Layer Neural Networks: Polynomial Convergence and SQ Lower Bounds. Proc. of Conference on Learning Theory. Phoenix, Arizona: Proceedings of Machine Learning Research, 2019.
Daniel Štefankovič, Eric Vigoda, and John Wilmes. On Counting Perfect Matchings in General Graphs. Proc. of Latin American Symposium on Theoretical Informatics. Buenos Aires, Argentina: Springer, 2018.