Andrew joined Galois in 2023 as a machine learning research engineer. He focuses on using statistical modeling and optimization methods to find solutions to real-world problems. Andrew earned his Ph.D. in applied mathematics from University of Maryland, College Park, where his research comprised combinatorial optimization algorithms with application to understanding nervous system development in embryonic Caenorhabditis elegans, a small roundworm. The multi-disciplinary work brought together physicists, biologists, and of course, a mathematician.
Beyond machine learning, he dedicates his time to staying active: cycling, yoga, and weight lifting. He is also always available to try out a new restaurant in the Washington, D.C. area.