Summary
Andrew Hands is a University of Chicago PhD student specializing in higher-order graph neural networks with 11 years of hands-on experience spanning research, teaching, and software development. His work bridges theoretical combinatorics and practical scalable learning—evidenced by an undergraduate project that converted Grimm's Conjecture into a finite-search algorithm proving cases up to interval length 31. He brings strong foundations in both computer science and mathematics (dual BS degrees, high honors) and practical exposure to computer vision, probabilistic active learning, and web development. As a research assistant and occasional instructor, he combines rigorous theory with reproducible experimental practice to tackle graph-structured and combinatorial problems at scale.
11 years of coding experience
1 year of employment as a software developer
Bachelor of Science - BS, Computer Science, 3.971, Bachelor of Science - BS, Computer Science, 3.971 at The University of Texas at Arlington
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at University of Chicago
Associate of Science - AS, Engineering Computer Science, 4.0, Associate of Science - AS, Engineering Computer Science, 4.0 at Amarillo College