Seo Taek Kong

I am a Ph.D. Candidate in the ECE department at the University of Illinois Urbana-Champaign, where I am fortunate to be advised by Prof. R. Srikant. My research draws on applied probability and control theory to develop non-asymptotic analyses of stochastic algorithms. This work spans three domains: stochastic gradient descent, reinforcement learning, and generative AI. By comparing stochastic approximation algorithms with discretized diffusions, I derive finite-time guarantees that characterize their behavior, and the same framework yields order-optimal noise schedules for sampling in generative diffusion models.

Alongside my academic work, I have built search engines at NVIDIA and Amazon. Before my Ph.D., I spent three years at VUNO Inc. developing deep learning models for medical imaging.