Anderson Ye Zhang

Anderson Ye Zhang
  • Assistant Professor of Statistics and Data Science
  • Assistant Professor of Computer and Information Science (secondary appointment)

Contact Information

  • office Address:

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

Research Interests: Group Synchronization, Spectral Analysis, Ranking from Pairwise Comparisons, Clustering and Mixture Models, Network Analysis, Mean Field Variational Inference

Links: Personal Website

Overview

Education

Ph.D. in Statistics and Data Science, Yale University, 2018
B.Sc. in Statistics, Zhejiang University, 2013

Academic Positions Held

Assistant Professor, Department of Statistics and Data Science, University of Pennsylvania, 2019-
William H. Kruskal Instructor, Department of Statistics, University of Chicago, 2018-2019

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Research

Teaching

Current Courses (Spring 2025)

  • CIS9990 - Master's Thesis

    For students working on an advanced research program leading to the completion of master's thesis requirements.

    CIS9990063

  • STAT4310 - Statistical Inference

    Graphical displays; one- and two-sample confidence intervals; one- and two-sample hypothesis tests; one- and two-way ANOVA; simple and multiple linear least-squares regression; nonlinear regression; variable selection; logistic regression; categorical data analysis; goodness-of-fit tests. A methodology course. This course does not have business applications but has significant overlap with STAT 1010 and 1020. This course may be taken concurrently with the prerequisite with instructor permission.

    STAT4310001 ( Syllabus )

  • STAT9710 - Intro To Linear Stat Mod

    Theory of the Gaussian Linear Model, with applications to illustrate and complement the theory. Distribution theory of standard tests and estimates in multiple regression and ANOVA models. Model selection and its consequences. Random effects, Bayes, empirical Bayes and minimax estimation for such models. Generalized (Log-linear) models for specific non-Gaussian settings.

    STAT9710001 ( 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.

  • CIS9990 - Master's Thesis

    For students working on an advanced research program leading to the completion of master's thesis requirements.

  • MATH4990 - Supervised Study

    Study under the direction of a faculty member. Intended for a limited number ofmathematics majors.

  • STAT4310 - Statistical Inference

    Graphical displays; one- and two-sample confidence intervals; one- and two-sample hypothesis tests; one- and two-way ANOVA; simple and multiple linear least-squares regression; nonlinear regression; variable selection; logistic regression; categorical data analysis; goodness-of-fit tests. A methodology course. This course does not have business applications but has significant overlap with STAT 1010 and 1020. This course may be taken concurrently with the prerequisite with instructor permission.

  • STAT9710 - Intro To Linear Stat Mod

    Theory of the Gaussian Linear Model, with applications to illustrate and complement the theory. Distribution theory of standard tests and estimates in multiple regression and ANOVA models. Model selection and its consequences. Random effects, Bayes, empirical Bayes and minimax estimation for such models. Generalized (Log-linear) models for specific non-Gaussian settings.

  • 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.

Awards and Honors

  • Sloan Research Fellowship in Mathematics, 2025
  • NSF CAREER Award, 2025
  • New Researcher Award, The 11th ICSA International Conference, 2019
  • Francis J. Anscombe Award, Department of Statistics and Data Science, Yale University, 2018
  • IBM Student Paper Award, The 29th New England Statistical Symposium, 2015
  • Chu Kochen Scholarship, Zhejiang University, 2012

Activity

Latest Research

Duc Nguyen and Ye Zhang (2025), A Novel and Optimal Spectral Method for Permutation Synchronization, IEEE Transactions on Information Theory (Accepted).
All Research