Tingran Gao
William H. Kruskal Instructor
Department of Statistics
University of Chicago
5747 S Ellis Avenue Jones 316
Chicago IL 60637-1441

Professional Employments

William H. Kruskal Instructor (Sep. 2017 — present)
Department of Statistics (Computational and Applied Mathematics Initiative), The University of Chicago

Visiting Assistant Professor (Aug. 2015 — Aug. 2017)
Department of Mathematics, Duke University

Education

Ph.D. Mathematics Duke University (2010—2015)

M.S. Computer Science Duke University (2013—2015)

B.S. Tsinghua University (2006—2010)

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Research Interests

  • Signal/Image/Geometry Processing in Applied and Computational Harmonic Analysis
  • Differential Geometry and Algebraic Topology of Massive, High-Dimensional Datasets
  • Nonparametric and High-Dimensional Statistics
  • Applied Mathematics and Statistics in Evolutionary Anthropology and Medical Data Analysis

Latest News

[2019-04-21] Paper "Multi-Frequency Phase Synchronization" with Zhizhen Zhao accepted by ICML 2019

[2019-04-14] Paper "The Geometry of Synchronization Problems and Learning Group Actions" with Jacek Brodzki and Sayan Mukherjee accepted by Discrete & Computational Geometry

[2019-03-22] Collaborative project "Predicting Shifts in Biological Growth Driven by Climate Change: A Geometric Deep Learning Approach" with Dr. Jablonski's Group in the Department of the Geophysical Sciences is selected for funding by the University of Chicago Center for Data and Computing (CDAC) Data Science Discovery Fund

[2019-02-12] Two Gaussian process landmarking papers published in the inaugural issue of the SIAM Journal on Mathematics of Data Science

[2019-02-04] New preprint "Uniform-in-Time Weak Error Analysis for Stochastic Gradient Descent Algorithms via Diffusion Approximation" with Yuanyuan Feng, Lei Li, Jian-Guo Liu, and Yulong Lu available on arxiv

[2019-01-24] New preprint "Multi-Frequency Phase Synchronization" with Zhizhen Zhao available on arxiv

[2019-01-08] Paper "Gaussian Process Landmarking on Manifolds" with Shahar Z. Kovalsky and Ingrid Daubechies accepted by SIAM Journal on Mathematics of Data Science (SIMODS)

[2018-12-27] Paper "Gaussian Process Landmarking for Three-Dimensional Geometric Morphometrics" with Shahar Z. Kovalsky, Doug M. Boyer, and Ingrid Daubechies accepted by SIAM Journal on Mathematics of Data Science (SIMODS)