Wanli Qiao

Wanli Qiao is an Associate Professor in the Department of Statistics at George Mason University. His research focuses on modern nonparametric statistics, geometric data analysis, machine learning, and extreme value theory, with applications to molecular biology. He holds a faculty position at the Fairfax campus, located in the Nguyen Engineering Building. His work is supported by the National Science Foundation.

Qiao's research emphasizes statistical inference on geometric structures embedded in point clouds, particularly studying protein energy landscapes' geometric and topological properties. Key areas include density ridges, cluster tree analysis, and algorithmic development for geometric data analysis. His methodologies bridge statistical theory with computational practice, addressing challenges in high-dimensional and functional data.

Selected publications highlight contributions to clustering algorithms (e.g., hill-climbing consistency, mean-shift adaptations) and theoretical advancements in density estimation, confidence region construction, and extreme value analysis on manifolds. Collaborations span computational biology and statistical physics, demonstrating interdisciplinary impact.