Yuefeng Han

Yuefeng Han is an Assistant Professor in the Department of Applied and Computational Mathematics and Statistics at the University of Notre Dame, part of the College of Science. He holds a Ph.D. in Statistics from the University of Chicago (2019), an M.Sc. in Statistics from the University of Chicago (2014), and a B.S. in Mathematics from Zhejiang University, China (2012). His research focuses on high-dimensional statistics, tensor data analysis, time series analysis, and statistical machine learning, with a particular emphasis on developing methodologies for complex, high-dimensional data structures and dynamic systems.

His work has led to contributions in tensor factor models, statistical inference for stochastic optimization, and applications in econometrics and climate science. Han has been recognized with awards including the Consulting Award (2016) and Senior Consultant distinction (2016) from the University of Chicago Department of Statistics, along with a fellowship during his doctoral studies. He has advised PhD and undergraduate students, including Ke Xu, Rui Sheng (co-advised), and Xianglu Zhu.

His publications span top journals like the Annals of Statistics, Journal of the Royal Statistical Society Series B, and the Journal of the American Statistical Association. Han also contributes to software development, notably the tensorTS R package for tensor time series analysis. His service includes reviewing for leading statistical journals and consulting projects addressing interdisciplinary challenges in neurobiology, linguistics, and environmental science.