Summary
Brian Wheatman is a software engineer and PhD candidate at Johns Hopkins with 11 years of industry and research experience blending high-performance systems, distributed algorithms, and practical engineering. He has interned repeatedly at Google across multiple summers building simulators, distributed solvers, ML pipelines, and OS ports, and has driven research-grade parallel graph algorithms as a postdoc at University of Chicago targeting million-core sparse supercomputers. Now at Jump Trading, he brings low-latency, scalable thinking from both academia and finance, with prior research at Lawrence Berkeley Labs on memory-efficient data structures and MIT work that sped up NP-hard TSP variants by an order of magnitude. Comfortable across systems, data engineering, and algorithm design, he has a track record of turning theoretical guarantees into high-performance, real-world implementations. Based in Chicago and trained at MIT and Johns Hopkins, he combines deep theoretical grounding with repeated production experience at top tech and research institutions. An interesting through-line: his work repeatedly targets making asymptotically hard problems practically fast and memory-efficient at scale.
11 years of coding experience
9 years of employment as a software developer
Master of Engineering - MEng, Computer Science, Master of Engineering - MEng, Computer Science at Massachusetts Institute of Technology
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Johns Hopkins Whiting School of Engineering
Germantown Academy