WANG, Ke

WANG, Ke is an Assistant Professor in the Department of Mathematics at The Hong Kong University of Science and Technology. His research interests include probabilistic combinatorics, random structures, and random matrix theory and its applications. He has contributed to various publications in areas such as random matrix theory, spectral distribution, and statistical inference. His work includes studies on singular subspace perturbation, non-backtracking matrices, and random restricted partitions. He is also involved in teaching courses such as MATH2421 Probability.

Ke Wang is a mathematician specializing in Probability, Combinatorics, and Random matrix theory. His research focuses on the statistical properties of eigenvalues and eigenvectors of random matrices, with applications in random graph analysis, covariance matrix estimation, and high-dimensional data modeling. Wang's work explores the behavior of singular subspaces under random perturbations and the universality of local eigenvalue statistics in random covariance matrices. His publications include studies on sparse random graphs, random projections, and the distribution of singular vectors in matrix denoising models. His research contributes to understanding the theoretical foundations of statistical inference and machine learning algorithms.