Weijie Su

Weijie Su
  • Assistant Professor of Statistics

Contact Information

  • office Address:

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

Research Interests: statistical machine learning, high-dimensional inference, large-scale multiple testing, optimization, and privacy-preserving data analysis.

Links: Personal Website

Overview

Education

Ph.D. in Statistics, Stanford University, 2016
B.S. in Mathematics, Peking University, 2011
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Research

Teaching

Current Courses

  • STAT405 - Stat Computing With R

    The goal of this course is to introduce students to the R programming language and related eco-system. This course will provide a skill-set that is in demand in both the research and business environments. In addition, R is a platform that is used and required in other advanced classes taught at Wharton, so that this class will prepare students for these higher level classes and electives.

    STAT405401 ( Syllabus )

    STAT405402 ( Syllabus )

    STAT405403 ( Syllabus )

    STAT405404 ( Syllabus )

  • STAT705 - Stat Computing With R

    The goal of this course is to introduce students to the R programming language and related eco-system. This course will provide a skill-set that is in demand in both the research and business environments. In addition, R is a platform that is used and required in other advanced classes taught at Wharton, so that this class will prepare students for these higher level classes and electives.

    STAT705401 ( Syllabus )

    STAT705402 ( Syllabus )

    STAT705403 ( Syllabus )

    STAT705404 ( Syllabus )

  • 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.

    STAT991302 ( Syllabus )

Past Courses

  • AMCS599 - INDEPENDENT STUDY

  • STAT405 - STAT COMPUTING WITH R

    The goal of this course is to introduce students to the R programming language and related eco-system. This course will provide a skill-set that is in demand in both the research and business environments. In addition, R is a platform that is used and required in other advanced classes taught at Wharton, so that this class will prepare students for these higher level classes and electives.

  • 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. This course may be taken concurrently with the prerequisite with instructor permission.

  • STAT511 - 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.

  • STAT705 - STAT COMPUTING WITH R

    The goal of this course is to introduce students to the R programming language and related eco-system. This course will provide a skill-set that is in demand in both the research and business environments. In addition, R is a platform that is used and required in other advanced classes taught at Wharton, so that this class will prepare students for these higher level classes and electives.

  • 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.

  • STAT995 - DISSERTATION

  • STAT999 - INDEPENDENT STUDY

    Written permission of instructor and the department course coordinator required to enroll.

Awards and Honors

Activity

Latest Research

Richard A. Berk, Andreas Buja, Lawrence D. Brown, Edward I. George, Arun Kumar Kuchibhotla, Weijie Su, Linda Zhao (2020), Assumption Lean Regression, American Statistician, (in press).
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