Tony Cai

Tony Cai
  • Daniel H. Silberberg Professor
  • Professor of Statistics and Data Science

Contact Information

  • office Address:

    405 Academic Research Building
    265 South 37th Street
    Philadelphia, PA 19104

Research Interests: Statistical machine learning, high-dimensional statistics, large-scale inference, functional data analysis, statistical decision theory, applications to genomics and financial econometrics

Links: Personal Website

Overview

Education

PhD, Cornell University, 1996

Career and Recent Professional Awards

  • President-elect, President, and Past President, Institute of Mathematical Statistics, 2023-2025
  • Noether Distinguished Scholar Award, American Statistical Association, 2023
  • Laplace Lecturer of the Bernoulli Society, 10th World Congress in Probability & Statistics, 2021
  • International Chinese Statistical Association Distinguished Achievement Award, 2019
  • Peter Whittle Lecturer, Cambridge University, 2018
  • ICCM Best Paper Award, 2018
  • President-elect, President, and Past President, the International Chinese Statistical Association, 2016-2018
  • Hermann Otto Hirschfeld Lecturer, Humboldt-Universität zu Berlin, 2012
  • Forum Lecturer, 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

Academic Positions Held

Wharton: 2000-present (named Dorothy Silberberg Professor, 2007).

For more information, go to My Personal Page

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Research

Teaching

Current Courses (Fall 2024)

  • STAT4300 - Probability

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

    STAT4300001 ( Syllabus )

    STAT4300002 ( Syllabus )

    STAT4300003 ( Syllabus )

All 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.

  • STAT9150 - Nonparametric Inference

    Statistical inference when the functional form of the distribution is not specified. Nonparametric function estimation, density estimation, survival analysis, contingency tables, association, and efficiency.

  • STAT9720 - Adv Topics in Math Stat

    A continuation of STAT 9700.

  • STAT9910 - Sem in Adv Appl of Stat

    This seminar will be taken by doctoral candidates after the completion of most of their coursework. Topics vary from year to year and are chosen from advance probability, statistical inference, robust methods, and decision theory with principal emphasis on applications.

  • STAT9950 - Dissertation

    Dissertation

Awards and Honors

Activity

Latest Research

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.
All Research

Wharton Magazine

Final Exam

Think you could still ace your way through Wharton? Well, here’s your chance to prove it.

Wharton Magazine - 09/01/2010