Anderson Ye Zhang

Anderson Ye Zhang
  • Assistant Professor of Statistics

Contact Information

  • office Address:

    444 Jon M. Huntsman Hall
    3730 Walnut Street
    Philadelphia, PA 19104

Research Interests: network analysis, mean field variational inference, theoretical guarantees of iterative algorithms, clustering and mixture models

Overview

Education

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

Academic Positions Held

William H. Kruskal Instructor, Department of Statistics, University of Chicago, 2018-2019

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Research

Teaching

Current Courses

  • STAT431 - 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 101 and 102.

    STAT431001 ( Syllabus )

    STAT431002 ( Syllabus )

Past Courses

  • STAT431 - 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 101 and 102.

  • STAT991 - 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.

Activity

Latest Research

Chao Gao, Zongming Ma, Ye Zhang, Harrison H. Zhou (2018), Community detection in degree-corrected block models, The Annals of Statistics, 46 (5), pp. 2153-2185.
All Research