Yinuo Ren
Kempner Institute Research Fellow
About
Yinuo Ren earned a Ph.D. in Applied and Computational Mathematics at Stanford University, supervised by Professors Lexing Ying and Grant M. Rotskoff. His research interests lie in the intersection of machine learning, stochastic analysis, and numerical analysis, with a focus on the mathematical foundations and algorithmic designs of generative models. He obtained his B.S. in Mathematics from Peking University, and completed internships at ByteDance Seed, Flatiron Institute, and Amazon.
Research Focus
Yinuo develops mathematically grounded and computationally efficient generative modeling methods at the intersection of stochastic processes, numerical analysis, and modern machine learning. His research aims to connect model design to representation power, training dynamics, and error behavior, enabling generative models that are interpretable and controllable, instead of pure data-driven black boxes. His ultimate goal is to transform generative models into domain-aware priors that support scalable inference and discovery across the natural and engineering sciences.