Yijun Dong (董一珺)

 

Courant Instructor/Assistant Professor (postdoc)
Courant Institute of Mathematical Sciences
New York University
Email: yd1319 [@] nyu [DOT] edu
Office: WWH 526, 251 Mercer St, New York, NY 10012

(Curriculum Vitae, Google Scholar, GitHub)

About Me

I am a Courant Instructor/Assistant Professor (postdoc) at the Courant Institute of New York University. I completed my PhD at the Oden Institute of UT Austin, advised by Prof. Per-Gunnar Martinsson and Prof. Rachel Ward.

My research bridges randomized numerical linear algebra and machine learning theory, with focuses on the computational and sample efficiency of algorithms for high-dimensional problems with low intrinsic dimensions. For computational efficiency, my work is centered on randomized algorithms for dimension reduction and low-rank approximation. For sample efficiency, my work focuses on the generalization and distributional robustness of learning algorithms in data-limited settings.

I will be on the 2025-2026 job market, looking for full-time academia and industry positions globally. Please feel free to reach out!

Selected Publications

(* denotes equal contribution or alphabetical order)

Education

Ph.D. in Computational Science, Engineering, and Mathematics, 2018 - 2023
Oden Institute for Computational Engineering and Sciences, UT Austin, Austin, Texas, US
Thesis: Randomized Dimension Reduction with Statistical Guarantees

B.S. in Applied Mathematics & Engineering Science, 2014 - 2018
Emory University, Atlanta, Georgia, US
Thesis: Crystals and Liquids in Gravitationally Confined Quasi-2-Dimensional Colloidal Systems