معرفی
Hailin Sang is an Associate Professor in the Department of Mathematics at the University of Mississippi, affiliated with the College of Liberal Arts. He holds a Ph.D. in Mathematics from the University of Connecticut (2008) and has previously held visiting assistant professor and postdoctoral research fellow positions at institutions including the University of Cincinnati, National Institute of Statistical Sciences/Duke University, and Indiana University.
Dr. Sang’s research spans theoretical and applied statistics, with emphasis on deep learning, probability theory, empirical processes, time series analysis, random fields, nonparametric and robust statistics, and self-normalized statistics. His work also extends to survey sampling design and analysis. Recent publications highlight applications in generative adversarial networks, modified ReLU networks, and entropy estimation, with methodological contributions to limit theorems and deviation bounds for complex stochastic structures.
His research has received partial support from the Simons Foundation. He has not been explicitly recognized for scientific awards in the provided text. Dr. Sang teaches a range of courses from elementary statistics to advanced statistics seminars, reflecting his broad educational contributions.
