Jian Huang is a chair professor of Data Science and Analytics in the Department of Applied Mathematics at the Hong Kong Polytechnic University. He earned his PhD in Statistics from the University of Washington in Seattle. His current research interests include deep generative models, statistical inference in deep learning, neural network approximation theory, representation learning, and statistical analysis using pretrained large models.

Huang has published extensively across various fields, including Statistics, Biostatistics, Machine Learning, Bioinformatics, and Econometrics. Recognized as a Highly Cited Researcher in Mathematics from 2015 to 2019 by the Web of Science Group, he has also been listed among the top 2% of the world’s most cited scientists by Elsevier BV and Stanford University from 2019 to 2024. He serves on the editorial boards of the Journal of the American Statistical Association and the Journal of the Royal Statistical Society: Series B and is a Fellow of both the American Statistical Association and the Institute of Mathematical Statistics.