Xiaohui Chen

Xiaohui Chen is an Associate Professor in the Department of Mathematics at the University of Southern California (USC), affiliated with the Master's Program in Mathematical Data Science. Previously, he held positions at the University of Illinois at Urbana-Champaign (UIUC), including Associate Professor (2019–present) and Assistant Professor (2013–2019), with a visiting role at MIT's IDSS in 2019–2020. His research focuses on high-dimensional statistics, machine learning, optimal transport, and quantum computing, with applications in signal processing and data science.

Education: PhD in Electrical and Computer Engineering from the University of British Columbia (2013). Awards include the NSF CAREER Award (2018), Simons Fellowship in Mathematics (2020–2021), and ICSA Outstanding Young Researcher Award (2019). His work bridges theoretical foundations with practical algorithms, such as diffusion K-means clustering and Wasserstein proximal optimization methods.

Key contributions include statistically optimal K-means clustering via semidefinite programming, analysis of density evolution from snapshot data, and quantum random state generation using holographic thermalization. He leads the Machine Intelligence Research Lab (MIRL) at USC, exploring machine learning and AI's mathematical underpinnings.