Published several papers including 'State evolution beyond first-order methods I: Rigorous predictions and finite-sample guarantees' (preprint) and 'Sharp global convergence guarantees for iterative nonconvex optimization: A Gaussian process perspective' (Annals of Statistics). Runner-up for Best paper prize for young researchers in continuous optimization by the Mathematical Optimization Society.
Research Experience
Held postdoctoral appointments at the University of Cambridge in the Department of Pure Mathematics and Mathematical Statistics and at the Georgia Institute of Technology in the Industrial and Systems Engineering department.
Education
PhD in Electrical Engineering from Stanford University and BS in Electrical Engineering and Computer Science from UC Berkeley.
Background
Assistant professor in the department of Data Sciences and Operations at the Marshall School of Business, University of Southern California (USC). Broadly interested in problems at the intersection of optimization, statistics, and computational complexity.
Miscellany
Previously published under the name Kabir Aladin Chandrasekher.