# 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.