Anderson Ye Zhang

Anderson Ye Zhang is an Assistant Professor in the Department of Statistics and Data Science at the Wharton School, University of Pennsylvania, with a secondary appointment in the Department of Computer and Information Science. He holds a PhD from Yale University and previously served as a William H. Kruskal Instructor at the University of Chicago. His research focuses on the theoretical and applied aspects of statistics and machine learning, emphasizing spectral methods, synchronization problems, clustering, and network analysis.

Education:

• PhD in Statistics and Data Science, Yale University (2018)
• Bachelor's degree from Zhejiang University (2012)

Research Interests: His work addresses foundational challenges in spectral analysis, group synchronization (e.g., phase synchronization, permutation synchronization), ranking systems, and high-dimensional clustering. He develops algorithms with provable guarantees for problems such as Gaussian mixture models, stochastic block models, and item response theory.

Recent Trends in Publications (2021–2025): His articles emphasize spectral methods for synchronization and clustering, with a focus on optimality in high-noise regimes, privacy-preserving learning, and efficient algorithms for complex data structures like human response models and anisotropic covariances. His work bridges statistical theory and computational practice.

Awards & Grants:

• 2025: Sloan Research Fellowship, NSF CAREER Award
• 2019: New Researcher Award (ICSA)
• 2018: Francis J. Anscombe Award

• NSF DMS-2440180 (CAREER: Statistical Inference in Group Actions)
• NSF DMS-2112988 (Ranking from Comparisons)

Academic Contributions: He has advised multiple collaborative research projects with postdocs and students, particularly on spectral methods and synchronization problems. His teaching spans advanced statistical theory and linear models at Wharton and the University of Chicago.