Summary
Rishi Sonthalia is an Assistant Professor specializing in the Mathematics of Deep Learning with nine years of experience applying combinatorics, analysis, and geometry to develop and analyze machine learning tools. He earned a PhD in Applied and Interdisciplinary Mathematics from the University of Michigan (Peter Smereka Award for Best Applied Math Thesis) after dual Computer Science and Mathematics degrees from Carnegie Mellon. Rishi’s work has been published at NeurIPS, JMLR, TMLR, Nature Machine Intelligence and other top venues, reflecting a blend of rigorous theory and practical ML insights. He has held research and teaching roles at UCLA, Max Planck Institute, Yale, and Michigan, bridging international collaborations and academic mentorship. Based in Los Angeles, he combines deep mathematical rigor with a knack for translating abstract theory into methods that illuminate modern deep learning phenomena.
8 years of coding experience
8 years of employment as a software developer
Doctor of Philosophy - PhD, Applied and Interdisciplinary Mathematics, Doctor of Philosophy - PhD, Applied and Interdisciplinary Mathematics at University of Michigan - Rackham Graduate School
Bachelor of Science with University Honors, Computer Science and Mathematics, Phi Beta Kappa; Phi Kappa Phi (top 10%), Bachelor of Science with University Honors, Computer Science and Mathematics, Phi Beta Kappa; Phi Kappa Phi (top 10%) at Carnegie Mellon University
English, Hindi, Spanish