Jianhao Ma

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Jianhao Ma
Ph.D. candidate at Department of Industrial and Operational Engineering
University of Michigan, Ann Arbor, United States

Email: jianhao [at] umich [dot] edu
[Google Scholar][Curriculem Vitae]

About me

I'm currently a fourth-year Ph.D. candidate at Umich. I am fortunate to be advised by Professor Salar Fattahi. My research focus on large-scale optimization and robust machine learning. I welcome future collaborations. Please feel free to contact me via Email!

Research Interests

  • General optimization and generalization in modern machine learning.

  • Algorithmic robust statistics.

  • Empirical process and its application.


  • Can Learning Be Explained By Local Optimality In Low-rank Matrix Recovery? [arxiv]
    INFORMS Junior Faculty Interest Group (JFIG) Paper Competition – Second Place
    Jianhao Ma, Salar Fattahi


  • Convergence of Gradient Descent with Small Initialization for Unregularized Matrix Completion [arxiv]
    Conference on Learning Theory (COLT) 2024
    Jianhao Ma, Salar Fattahi

  • Robust Sparse Mean Estimation via Incremental Learning [arxiv]
    ICLR Workshop on Bridging the Gap Between Practice and Theory in Deep Learning 2024
    Jianhao Ma, Rui Ray Chen, Yinghui He, Salar Fattahi, Wei Hu

  • Global Convergence of Sub-gradient Method for Robust Matrix Recovery: Small Initialization, Noisy Measurements, and Over-parameterization [arxiv]
    Journal of Machine Learning Research (JMLR) 2023
    Jianhao Ma, Salar Fattahi

  • Behind the Scenes of Gradient Descent: A Trajectory Analysis via Basis Function Decomposition [arxiv]
    International Conference on Learning Representations (ICLR) 2023
    Jianhao Ma, Lingjun Guo, Salar Fattahi

  • Blessing of Nonconvexity in Deep Linear Models: Depth Flattens the Optimization Landscape Around the True Solution [arxiv]
    Advances in Neural Information Processing Systems (NeurIPS) 2022 (Spotlight)
    Katta Murty Prize for Best Research Paper on Optimization (IOE Department)
    Jianhao Ma, Salar Fattahi

  • Towards Understanding Generalization via Decomposing Excess Risk Dynamics [paper] [arxiv]
    International Conference on Learning Representations (ICLR) 2022
    Jiaye Teng*, Jianhao Ma*, Yang Yuan

  • Sign-RIP: A Robust Restricted Isometry Property for Low-rank Matrix Recovery [paper][arxiv]
    Jianhao Ma, Salar Fattahi
    NeurIPS Workshop on Optimization for Machine Learning, 2021


  • March 2024: I will attend INFORMS Optimization Society Conference.

  • March 2024: Our paper has been accepted at ICLR BGPT workshop.

  • March 2024: Thrilled to receive Rackham Predoctoral Fellowship.

  • February 2024: I will intern at FAIR Labs in Meta with Lin Xiao this summer.

  • February 2024: New paper about the global convergence of GD for unregularized matrix completion.




Always consider a problem under the minimum structure in which it makes sense. —— Gustave Choquet