Anderson Ye Zhang

Anderson Ye Zhang is an Assistant Professor of Statistics and Data Science at the University of Pennsylvania, with a secondary appointment in Computer and Information Science. His research focuses on Group Synchronization, Spectral Analysis, Ranking from Pairwise Comparisons, Clustering and Mixture Models, Network Analysis, and Mean Field Variational Inference. He is affiliated with the Department of Statistics and Data Science at Wharton. His work has been published in top-tier journals and conferences, including the SIAM Journal on Optimization, IEEE Transactions on Information Theory, and NeurIPS. Zhang's research explores theoretical and methodological advancements in statistical learning and data science.

Anderson Ye Zhang is an Assistant Professor of Statistics and Data Science at the University of Pennsylvania, specializing in Statistics and Machine Learning. His research focuses on theoretical and computational aspects of statistical inference, particularly in community detection, clustering, and ranking problems. He investigates the performance of algorithms in models such as stochastic block models, Gaussian mixture models, and Bradley–Terry–Luce models. His work emphasizes achieving optimal statistical rates and understanding the limits of recovery in structured data. Zhang's research also explores uncertainty quantification and privacy-preserving learning from human response data.