Buyun Liang

Buyun Liang

Computer Science M.S. Student

University of Minnesota, Twin Cities


I am a M.S. student in the Department of Computer Science & Engineering at the University of Minnesota, Twin Cities, also work as a graduate research assistant in Prof. Ju Sun’s group.

Broadly, my research is about deep learning, optimization, and robustness. Specifically, I am interested in: 1). User-friendly and scalable software for constrained optimization in deep learning; 2). Robustness issue in computer vision; 3). Deep learning with non-trivial constraints.

Prior to this, I obtained my first M.S. degree in Materials Science at the University of Minnesota, Twin Cities, and my B.S. degree from the School of Physics, Nanjing University. Before joining Prof. Ju Sun’s group, I worked as a research assistant in Prof. J. Ilja Siepmann’s computational chemistry group.

Download my Curriculum Vitae.

  • Optimization Software
  • Robustness of Deep Learning
  • Constrained Deep Learning
  • M.S. in Computer Science, 2020 - Present

    University of Minnesota, Minneapolis, MN, USA πŸ‡ΊπŸ‡Έ

  • M.S. in Materials Science, 2018 - 2020

    University of Minnesota, Minneapolis, MN, USA πŸ‡ΊπŸ‡Έ

  • B.S. in Physics, 2014 - 2018

    Nanjing University, Nanjing, China πŸ‡¨πŸ‡³

Recent News

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[Sep 19, 2022] To be a Reviewer for the 26th International Conference on Artificial Intelligence and Statistics (AISTATS 2023).

[Jul 27, 2022] We (speaker: Prof. Ju Sun) introduced NCVX PyGRANSO and its practical applications and tricks in the Nonsmooth Optimization in Machine Learning session in the International Conference on Continuous Optimization (ICCOPT), 2022. See the talk slides for more details!

[Jul 26, 2022] NCVX PyGRANSO v1.2.0 released. Check our Change Log here!


NCVX (NonConVeX) is a user-friendly and scalable python software package targeting general nonsmooth NCVX problems with nonsmooth constraints.