Dr. Hailin Sang is a Professor of Mathematics in the Department of Mathematics at the University of Mississippi.
Research Interests
Dr. Hailin Sang’s research focuses on theory and application of statistics, deep learning and probability.
He is also interested in:
- Deep learning, Empirical Processes
- Time Series, Random Fields
- Nonparametric Statistics, Robust Statistics, Self-normalized Statistics
- Survey Sampling Design & Analysis
Biography
Dr. Hailin Sang is an associate professor in the Department of Mathematics at the University of Mississippi. He finished a Ph.D. in 2008 from University of Connecticut under the supervision of Evarist Giné. Before he joined University of Mississippi in 2012, he worked as a visiting assistant professor or postdoc research fellow at University of Cincinnati, National Institute of Statistical Sciences/Duke University and Indiana University. His research is partially supported by Simons Foundation.
Publications
Selected Publications:
Limit theorems for linear random fields with innovations in the domain of attraction of a stable law, M. Peligrad, H. Sang, Y. Xiao and G. Yang, Stochastic Processes and their Applications, accepted.
A Local limit theorem for linear random fields, T. Fortune, M. Peligrad and H. Sang, Journal of Time Series Analysis, 42 (2021), no. 5-6, 696-710.
Cramér type moderate deviations for random fields, A. Beknazaryan, H. Sang and Y. Xiao, Journal of Applied Probability, 56 (2019), no. 1, 223-245.
Kernel entropy estimation for linear processes, H. Sang, Y. Sang and F. Xu, Journal of Time Series Analysis, 39 (2018), no. 4, 563-591.
Symmetric Gini-covariance and correlation coefficient, Y. Sang, X. Dang and H. Sang, The Canadian Journal of Statistics, 44 (2016), 323-342.
Exact moderate and large deviations for linear processes, M. Peligrad, H. Sang, Y. Zhong and W. B. Wu, Statistica Sinica, 24 (2014), 957-969.
Asymptotic properties of self-normalized linear processes with long memory, M. Peligrad and H. Sang, Econometric Theory, 28 (2012), 3, 548-569.
Uniform asymptotics for kernel density estimators with variable bandwidths, E. Giné and H. Sang, Journal of Nonparametric Statistics, 22 (2010), 6, 773-795.
Courses Taught
- Math 115 Elementary Statistics
- Math 261 Unified Calculus & Analytic Geometry I
- Math 262 Unified Calculus & Analytic Geometry II
- Math 263 Unified Calculus & Analytic Geometry III
- Math 264 Unified Calculus & Analytic Geometry IV
- Math 267 Calculus for Business, Econ., & Accy. I
- Math 375 Introduction to Statistics I
- Math 575 Mathematical Statistics I
- Math 576 Mathematical Statistics II
- Math 671 Statistical Methods I
- Math 672 Statistical Methods II
- Math 775 Advanced Statistics I
- Math 777 Seminar in Statistics
Education
Ph.D. Mathematics, University of Connecticut (2008)