Professor Tengyao Wang

About

Tengyao Wang is broadly interested in the area of high-dimensional statistics. His research focuses mainly on developing computationally efficient procedures for high-dimensional problems, while at the same time understanding the potential statistical limitations imposed by computational constraints. Some of his current research interests include: (i) Sparse signal detection in high-dimensional data; (ii) Change-point detection and estimation problems; (iii) Dimension reduction techniques; (iv) Robust statistical procedures in the presence of missing data or heavy-tailed noise; (v) Nonparametric statistical inference and (vi) Applications, including medical statistics, financial data analysis and statistical learning-assisted material discovery.