Yingying Fan, University of Southern California

Yingying Fan is Associate Dean for the PhD Program, Centennial Chair in Business Administration, Professor in Data Sciences and Operations Department of the Marshall School of Business at the University of Southern California. She received her Ph.D. in Operations Research and Financial Engineering from Princeton University in 2007. She was a Lecturer in the Department of Statistics at Harvard University from 2007-2008 and Dean's Associate Professor in Business Administration at USC from 2018-2021.

Her research interests include statistics, data science, machine learning, economics, and big data and business applications. Her latest works have focused on statistical inference for networks, texts, and AI models empowered by some most recent developments in random matrix theory and statistical learning theory. She is the recipient of the Institute of Mathematical Statistics Medallion Lecture, Fellow of Institute of Mathematical Statistics, Fellow of American Statistical Association, the Royal Statistical Society Guy Medal in Bronze, the American Statistical Association Noether Young Scholar Award, and the NSF Faculty Early Career Development (CAREER) Award. She has served as an IMS Editor of Statistics Surveys and an associate editor of The Annals of Statistics, Information and Inference, Journal of Business & Economic Statistics, Journal of Econometrics, Journal of the American Statistical Association, Journal of Multivariate Analysis (2013-2016), and The Econometrics Journal (2012-2023).

Huazhen Lin, Southwestern University of Finance and Economics

Huazhen Lin is the Chair Professor at the Southwestern University of Finance and Economics (SWUFE) and the director of the Center of Statistical Research at SWUFE. She is a New Cornerstone Investigator，a fellow of the Institute of Mathematical Statistics, a Distinguished Professor of Changjiang Scholars appointed by the Chinese Ministry of Education, and a recipient of the National Science Fund for Distinguished Young Scholars.

Huazhen Lin's main research interests include deep learning, nonparametric method, survival data analysis, functional data analysis, factor model, and transformation model. She has published numerous research papers in internationally renowned statistics journals, including Annals of Statistics, Journal of the American Statistical Association, Journal of the Royal Statistical Society: Series B, and Biometrika. 

Huazhen Lin currently serves as an associate editor for the Journal of the American Statistical Association and has held similar roles for various other journals, such as Biometrics,  the Scandinavian Journal of Statistics, the Journal of Business & Economic Statistics, the Canadian Journal of Statistics,  Statistics and Its Interface, and Statistical Theory and Related Fields. She also serves on the editorial boards of various Chinese journals, such as the English Series of Acta Mathematica Sinica, the Chinese Journal of Applied Probability and Statistics, the Journal of Systems Science and Mathematical Sciences, and the Journal of Applications of Statistics and Management.

Additionally, she is a board member of the International Chinese Statistical Association (ICSA), an associate director of the Chinese Association for Applied Statistics (CAAS), the director of the Data Science and Artificial Intelligence Chapter at CAAS, and an associate chair of the Chinese Association for Industrial Statistics Teaching.