Areas of Interest
Biostatistics, Machine Learning, Ultrahigh-dimensional Variable/Feature Selection and Inference, Shape Analysis, Longitudinal/Functional Data Analysis, Biomedical Applications
Research
My main focus is to develop advanced statistical models and computational methodologies to unravel the genetic and environmental mechanisms that regulate complex biological traits, including morphology/shape, biomedical problems and disease. I am particularly interested in high-dimensional, "big data" modeling, and functional data analysis. My genetic leaf shape project was awarded a three-year NSF grant. I enjoy collaborating on interdisciplinary projects, working with researchers from the application domains and addressing real-life data analysis questions.
Courses
Fall 2026
| Course |
Section |
Title |
Schedule |
Room |
| Math 485A |
01 |
Undergraduate Research Seminar |
TR 9:45–11:15
|
OO-G062
|
Ph.D. Students
-
Shaofei Zhao,
Summer, 2022
— Theory and application about variable selection approaches for high dimensional genomic data
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