Summary
Max Simchowitz is an assistant professor and former MIT CSAIL postdoctoral researcher with nine years of experience at the intersection of robotics, machine learning, and spectral methods. He earned a PhD in Computer Science from UC Berkeley and has a track record of research-driven engineering from Princeton and Columbia to industry internships, applying tensor and graph-spectral techniques to problems from Poisson factorization to event detection. At MIT he focused on robot locomotion, translating theoretical tools into practical algorithms for control and perception, and now leads academic work at Carnegie Mellon. Known for bridging deep theoretical insight with production-minded implementations, he often pairs spectral/algebraic methods with optimized code across languages. Based in Los Angeles, he brings a rare blend of mathematical rigor and hands-on systems experience to robotics and ML research.
9 years of coding experience
1 year of employment as a software developer
Doctor of Philosophy (PhD) Computer Science, Doctor of Philosophy (PhD) Computer Science at University of California, Berkeley
Bachelor of Arts (B.A.) Mathematics, Bachelor of Arts (B.A.) Mathematics at Princeton University