Rate My Professor Hang Zhou

Hang Zhou is an Assistant Professor in the School of Data Science and Society with a joint appointment in the Department of Statistics and Operations Research at the University of North Carolina at Chapel Hill. He received his Ph.D. in Statistics from the School of Mathematical Sciences at Peking University in 2022, where he was advised by Professor Fang Yao. Before joining UNC-Chapel Hill, Zhou was a postdoctoral researcher in the Department of Statistics at the University of California, Davis, working with Professors Hans-Georg Müller and Jane-Ling Wang. His academic career focuses on advancing statistical methodologies for complex data structures encountered in modern applications.

Zhou's research specializations include functional and longitudinal data analysis, statistical inference for object-valued data such as distributions, trees, and compositional data, learning theory including generalization bounds for deep neural networks, and model-agnostic methods with applications like anomaly detection. He has published extensively in leading statistical journals. Notable publications include 'Theory of functional principal component analysis for noisy and discretely observed data' (Annals of Statistics, 2025, with Dongyi Wei and Fang Yao), 'Conformal inference for random objects' (Annals of Statistics, 2025, with Hans-Georg Müller), 'Deep regression for repeated measurements' (Journal of the American Statistical Association, 2025, with Shunxing Yan and Fang Yao), 'Wasserstein-Fréchet Integration of Conditional Distributions' (Electronic Journal of Statistics, 2025, with Álvaro Gajardo and Hans-Georg Müller), 'Functional linear regression for discretely observed data: from ideal to reality' (Biometrika, 2023, with Fang Yao and Huiming Zhang), and 'Intrinsic Wasserstein Correlation Analysis' (Statistica Sinica, in press 2025+, with Zhenhua Lin and Fang Yao). Additional contributions appear in the Journal of Data-centric Machine Learning Research (2024) and IEEE Transactions on Pattern Analysis and Machine Intelligence (2024). Zhou has also presented at major conferences including ICML (2024), NeurIPS (2024), ACM KDD (2025), and ACM Multimedia (2025).