Yijun Dong (董一珺)
About MeI 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) EducationPh.D. in Computational Science, Engineering, and Mathematics, 2018 - 2023 B.S. in Applied Mathematics & Engineering Science, 2014 - 2018 |