Buyun Liang

Buyun Liang (梁步云)

M.S. Student
Department of Computer Science & Engineering
University of Minnesota, Twin Cities
Minneapolis, MN, 55455


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 optimization in machine/deep learning and machine/deep learning in vision.

Specifically, I am interested in:

  1. User-friendly and scalable software for nonconvex optimization in machine/deep learning.

  2. Deep Learning with deterministic and stochastic constraints.

  3. Learning in distributed and collaborative environments.

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.

Updates

[Feb 20, 2022] PyGRANSO v1.1.0 released. Join our NCVX PyGRANSO Forum for more information!

[Feb 12, 2022] Completed my third Powerlifting meet! Check this page for more details. See my instagram for my daily training videos.

[Jan 07, 2022] Our NCVX package is highlighted in Research Computing (Office of the Vice President for Research)

[Jan 01, 2022] NCVX with its initial solver PyGRANSO v1.0.0 released. Check the documentation page and GitHub repo for more information.

[Nov 29, 2021] Proud to release our paper NCVX: A User-Friendly and Scalable Package for Nonconvex Optimization in Machine Learning on arXiv! NCVX is the initial translation and revamping of the GRANSO package, with convenient features such as auto-differentiation and GPU support. In particular, NCVX can be used to solve constrained deep learning problems.

[May 25, 2021] I am funded by the U of M Informatics Institute (UMII) Seed Grant Program to revamp the GRANSO package into a user-friendly, scalable numerical optimization package.