Yijun Dong (董一珺)

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 lies in randomized numerical linear algebra and learning theory. I am broadly interested in high-dimensional problems with low intrinsic dimensions, with focuses on the computational and sample efficiency of algorithms in machine learning and scientific computing. 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

• Discrepancies are Virtue: Weak-to-Strong Generalization through Lens of Intrinsic Dimension.
  Yijun Dong, Yicheng Li, Yunai Li, Jason D. Lee, Qi Lei.
  ICML 2025.
  

• Robust Blockwise Random Pivoting: Fast and Accurate Adaptive Interpolative Decomposition.
  Yijun Dong, Chao Chen, Per-Gunnar Martinsson, Katherine Pearce.
  SIAM Journal on Matrix Analysis and Applications 2025. [GitHub]
  

• Sketchy Moment Matching: Toward Fast and Provable Data Selection for Finetuning.
  Yijun Dong*, Hoang Phan*, Xiang Pan*, Qi Lei.
  NeurIPS 2024. [GitHub]
  

• Efficient Bounds and Estimates for Canonical Angles in Randomized Subspace Approximations.
  Yijun Dong, Per-Gunnar Martinsson, Yuji Nakatsukasa.
  SIAM Journal on Matrix Analysis and Applications 2024. [GitHub]
  

• Cluster-aware Semi-supervised Learning: Relational Knowledge Distillation Provably Learns Clustering.
  Yijun Dong*, Kevin Miller*, Qi Lei, Rachel Ward.
  NeurIPS 2023. [GitHub]
  

• Sample Efficiency of Data Augmentation Consistency Regularization.
  Shuo Yang*, Yijun Dong*, Rachel Ward, Inderjit Dhillon, Sujay Sanghavi, Qi Lei.
  AISTATS 2023. [pmlr]
  

• Simpler is better: A comparative study of randomized algorithms for computing the CUR decomposition.
  Yijun Dong, Per-Gunnar Martinsson.
  Advances in Computational Mathematics 2023. [GitHub]
  

(* 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