Renjie Feng

Renjie Feng is a Research Fellow in Mathematics and AI at the School of Mathematics and Statistics and the Sydney Mathematical Research Institute, University of Sydney. His work bridges probability theory, statistics, and applications in machine learning, deep learning, and artificial intelligence.

His research interests focus on probability theory and its applications to machine learning, random matrix theory, and statistical physics. He investigates extreme value problems, spectral properties of random matrices, and topological features of random fields over Riemannian manifolds.

Recent publications highlight trends in random matrix theory (GUE, GOE, GSE), extreme gap problems, determinantal point processes, and Wiener chaos. Collaborative works with F. Götze, D. Yao, and R. Adler emphasize U-statistics, multivariate linear statistics, and random topology inspired by Poisson point process studies.