
About
Shizhe Chen is an Assistant Professor in the Department of Statistics at the University of California, Davis. His research focuses on statistical methodology for high-dimensional data, point processes, network reconstruction, and machine learning applications in neuroscience and biostatistics. He holds a Ph.D. and teaches advanced statistical courses such as STA 290. His work emphasizes flexible modeling approaches for complex systems and nonparametric methods for independence testing.
Key research interests include:
- High-dimensional statistical inference and graphical models
- Point process modeling with applications to neuroscience and social networks
- Development of assumption-light screening techniques for Hawkes processes
- Network reconstruction using ordinary differential equations
Recent work explores temporal dynamics in hippocampal sequences and distribution-free statistical tests for modern data structures. His methods bridge theoretical advancements with practical applications in computational biology and econometrics.
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