Jian Huang is a Chair Professor of Data Science and Analytics in the Department of Applied Mathematics at The Hong Kong Polytechnic University. He obtained his Ph.D. degree in Statistics from the University of Washington in Seattle. His current research interests include deep generative models and inference, statistical inference in deep learning, deep neural network approximation theory, representation learning, and statistical analysis leveraging pretrained large models. He has published widely in the fields of Statistics, Biostatistics, Machine Learning, Bioinformatics and Econometrics. He was designated a highly cited researcher in the field of Mathematics from 2015 to 2019 by the Web of Science group at Clarivate and included in the list of top 2% of the world's most cited scientists by Elsevier BV and Stanford University (2019-2024). He serves on the editorial boards of the Journal of the American Statistical Association and Journal of the Royal Statistical Society (Series B). Professor Huang is a fellow of the American Statistical Association and a fellow of the Institute of Mathematical Statistics.

Publications: Jian Huang's Google Scholar page