Tony Cai

• Tony Cai, Rungang Han, Anru Zhang (2022), On the Non-asymptotic Concentration of Heteroskedastic Wishart-type Matrix, Electronic Journal of Probability, 27 (), pp. 1-40.
• Anru Zhang, Tony Cai, Yihong Wu (2022), Heteroskedastic PCA: Algorithm, Optimality, and Applications, Annals of Statistics, 50 (1), pp. 53-80.
• Zijian Guo, Claude Renaux, Peter Bühlmann, Tony Cai (2021), Group Inference in High Dimensions with Applications to Hierarchical Testing, Electronic Journal of Statistics, 15 (), pp. 6633-6676.
• Sai Li, Tony Cai, Hongzhe Li (Under Review), Inference for High-dimensional Linear Mixed-effects Models: A Quasi-likelihood Approach.
• Tony Cai and Linjun Zhang (Under Review), A Convex Optimization Approach to High-dimensional Sparse Quadratic Discriminant Analysis.
• Rong Ma, Tony Cai, Hongzhe Li (2020), Global and Simultaneous Hypothesis Testing for High-Dimensional Logistic Regression Models, Journal of the American Statistical Association, (to appear) ().
• Tony Cai, Xiao Han, Guangming Pan (2020), Limiting Laws for Divergent Spiked Eigenvalues and Largest Non-spiked Eigenvalue of Sample Covariance Matrices, Annals of Statistics, (to appear) ().
• Tony Cai, Yichen Wang, Linjun Zhang (Under Review), The Cost of Privacy: Optimal Rates of Convergence for Parameter Estimation with Differential Privacy.
• Hyunseung Kang, Tony Cai, Dylan Small (Under Review), Robust Confidence Intervals for Causal Effects with Possibly Invalid Instruments.
• Tianxi Cai, Tony Cai, Zijian Guo (Under Review), Individualized Treatment Selection: An Optimal Hypothesis Testing Approach In High-dimensional Models.
• All Research from Tony Cai »

Past Courses

• AMCS5999 - Independent Study

  Independent Study allows students to pursue academic interests not available in regularly offered courses. Students must consult with their academic advisor to formulate a project directly related to the student’s research interests. All independent study courses are subject to the approval of the AMCS Graduate Group Chair.

• AMCS9999 - Ind Study & Research

  Study under the direction of a faculty member.

• STAT4300 - Probability

  Discrete and continuous sample spaces and probability; random variables, distributions, independence; expectation and generating functions; Markov chains and recurrence theory.

• STAT5100 - Probability

  Elements of matrix algebra. Discrete and continuous random variables and their distributions. Moments and moment generating functions. Joint distributions. Functions and transformations of random variables. Law of large numbers and the central limit theorem. Point estimation: sufficiency, maximum likelihood, minimum variance. Confidence intervals. A one-year course in calculus is recommended.

• STAT9720 - Adv Topics in Math Stat

  A continuation of STAT 9700.

• STAT9910 - Sem in Adv Appl of Stat

  This seminar is for graduate students who wish to learn about current research frontiers. It covers advanced topics in probability, statistical theory and methods, applied statistics, data science and artificial intelligence. Specific topics vary from year to year and emphasize both theoretical foundations and applications.

• STAT9950 - Dissertation

  Dissertation

• Leo Breiman Senior Award, 2026
• Fellow, American Association for the Advancement of Science, 2023
• Peter Whittle Lecture, Cambridge University, 2018
• Hermann Otto Hirschfeld Lectures, Humboldt-Universitat zu Berlin, 2012
• Forum Lecture, 28th European Meeting of Statisticians, Piraeus, Greece, 2010
• Medallion Lecturer, Institute of Mathematical Statistics, 2009
• The COPSS Presidents' Award, Committee of Presidents of Statistical Societies, 2008
• Fellow, Institute of Mathematical Statistics, 2006
• International Chinese Statistical Association Distinguished Achievement Award, 1970
• Laplace Lecture, Bernoulli Society, 10th World Congress in Probability & Statistics, 1970
• International Chinese Statistical Association Distinguished Achievement Award, 1970
• International Chinese Statistical Association Outstanding Service Award, 1970

Knowledge @ Wharton

• AI Is Killing the Cover Letter, Knowledge @ Wharton - 02/24/2026
• When Does AI Assistance Undermine Learning?, Knowledge @ Wharton - 02/24/2026
• How AI Is Reshaping Human Intuition and Reasoning | Gideon Nave and Steven Shaw, Knowledge @ Wharton - 02/24/2026
• Consumer Cryptocurrency Confidence Report 2025, Knowledge @ Wharton - 02/23/2026
• How Geopolitics Is Hitting Local Gas Stations, Knowledge @ Wharton - 02/20/2026
• Zillow’s VP of Brand and Product Marketing, Beverly Jackson, Knowledge @ Wharton - 02/19/2026
• Why Hiring Has Slowed Without Mass Layoffs, Knowledge @ Wharton - 02/18/2026
• NBA Analytics, Tanking, and the Future of Team Building, Knowledge @ Wharton - 02/18/2026
• How ‘Lemon Shocks’ Hurt Aggregate Investment, Knowledge @ Wharton - 02/17/2026
• Leading With Grounded Confidence, Knowledge @ Wharton - 02/17/2026