Jian Ding

Jian Ding
  • (On Leave in Spring 2022)
  • Gilbert Helman Professor
  • Professor of Statistics and Data Science
  • Professor of Mathematics (secondary appointment)

Contact Information

  • office Address:

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

Research Interests: Probability theory with focus on interactions with statistical physics and theory of computer science. In particular, extreme values of Gaussian processes, random constraint satisfaction problems, random planar geometry.

Links: CV



PhD, Statistics/Probability theory
UC Berkeley, 2006-2011
Advisor: Yuval Peres

B.S., Mathematics
Peking University, 2002-2006

Academic Positions Held

Professor, Department of Statistics and Data Science, University of Pennsylvania, 2021-

Associate Professor, Department of Statistics, University of Pennsylvania, 2017-2021

Associate Professor, Department of Statistics, University of Chicago, 2016-2017

Assistant Professor, Department of Statistics, University of Chicago, 2011-2016

Szego Assistant Professor, Department of Mathematics, Stanford University, 2011-2012

Postdoc, University of Washington, Summer 2011
Mentor: James Lee

Research Intern, Microsoft Research New England, Summer 2010
Mentor: Jennifer Chayes


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All Courses

  • AMCS9999 - Ind Study & Research

    Study under the direction of a faculty member.

  • STAT3990 - Independent Study

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

  • 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.

  • 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

  • STAT9990 - Independent Study

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

Awards and Honors

  • Invited Address in the AMS Sectional Meeting, Boston, MA, 2018 Description

    The AMS holds eight sectional meetings annually. Generally, there is one meeting in the spring and one in the fall in each section of the U.S.

  • Rollo Davidson Prize, 2017 Description

    The Rollo Davidson Prize is a prize awarded annually to early-career probabilists by the Rollo Davidson trustees. It is named after English mathematician Rollo Davidson (1944–1970).

  • Alfred P. Sloan Fellowship, 2015-2017 Description
    The Sloan Research Fellowships seek to stimulate fundamental research by early-career scientists and scholars of outstanding promise. These two-year fellowships are awarded yearly to 126 researchers in recognition of distinguished performance and a unique potential to make substantial contributions to their field.

  • NSF Career Award, 2015-2020 Description

    The Faculty Early Career Development (CAREER) Program is a Foundation-wide activity that offers the National Science Foundation’s most prestigious awards in support of early-career faculty who have the potential to serve as academic role models in research and education and to lead advances in the mission of their department or organization.


Latest Research

Jian Ding, Ryoki Fukushima, Rongfeng Sun, Changji Xu (2021), Distribution of the random walk conditioned on survival among quenched Bernoulli obstacles, Annals of Probability, (to appear).
All Research