Buyun Liang

Incoming Computer and Information Science Ph.D. Student

University of Pennsylvania

Biography

I am an incoming Computer and Information Science Ph.D. student at the University of Pennsylvania, advised by Prof. René Vidal. I am also a M.S. student in the Department of Computer Science & Engineering at the University of Minnesota, Twin Cities, advised by Prof. Ju Sun. My research interests have spanned optimization for AI, trustworthy AI and AI for science.

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 .

Interests

Optimization for AI
Trustworthy AI
AI for Science

Education

Ph.D. in Computer and Information Science, 2023 -
University of Pennsylvania, Philadelphia, PA, USA 🇺🇸
M.S. in Computer Science, 2020 - 2023
University of Minnesota, Minneapolis, MN, USA 🇺🇸
M.S. in Materials Science, 2018 - 2020
University of Minnesota, Minneapolis, MN, USA 🇺🇸
B.S. in Physics, 2014 - 2018
Nanjing University, Nanjing, Jiangsu, China 🇨🇳

Recent News

All news »

Upcoming tutorial: Tutorial on Deep Learning with Nontrivial Constraints in the SIAM International Conference on Data Mining (SDM23). (Apr 29, 2023)

Paper release: Proud to release our paper Optimization and Optimizers for Adversarial Robustness on arXiv! We have created the first general-purpose method for evaluating adversarial robustness and challenged the reliability of the existing robustness evaluation and adversarial training frameworks. (Mar 24, 2023)

Paper acceptance: Our paper Implications of Solution Patterns on Adversarial Robustness has been accepted by Computer Vision and Pattern Recognition (CVPR) Workshop of Adversarial Machine Learning on Computer Vision: Art of Robustness! (Mar 22, 2023)

I am thrilled to join Prof. René Vidal’s group as a Computer and Information Science Ph.D. student at the University of Pennsylvania this Fall! (Feb 28, 2023)

Paper acceptance: Our paper Optimization for Robustness Evaluation beyond ℓp Metrics has been accepted by IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2023)! (Feb 16, 2023)

Publications

Buyun Liang, Wenjie Zhang, Hengyue Liang, Tim Mitchell, Ying Cui, Ju Sun (2023). NCVX: A General-Purpose Optimization Solver for Machine Learning, and Practical Techniques. In preparation for IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI).

Website ICCOPT22 Slides SDM2023 Tutorial ICASSP 2023 Tutorial

Hengyue Liang, Buyun Liang, Le Peng, Ying Cui, Tim Mitchell, Ju Sun (2023). Optimization for Adversarial Robustness Evaluations and Implications from the Solution Patterns. Under review at International Journal of Computer Vision (IJCV).

Paper

Hengyue Liang, Buyun Liang, Le Peng, Ying Cui, Tim Mitchell, Ju Sun (2023). Implications of Solution Patterns on Adversarial Robustness. In Computer Vision and Pattern Recognition (CVPR) Workshop of Adversarial Machine Learning on Computer Vision (Art of Robustness).

Paper

Buyun Liang, Ryan de Vera, Hengyue Liang, Ying Cui, Tim Mitchell, Qizhi He, Ju Sun (2023). Neural Topology Optimization with Principled Constrained Optimization. In preparation for Structural and Multidisciplinary Optimization.

Buyun Liang, Tim Mitchell, Ju Sun (2022). NCVX: A General-Purpose Optimization Solver for Constrained Machine and Deep Learning. In Neural Information Processing Systems (NeurIPS) Workshop on Optimization for Machine Learning (OPT 2022).

Paper Poster

Hengyue Liang, Buyun Liang, Ying Cui, Tim Mitchell, Ju Sun (2022). Optimization for Robustness Evaluation beyond ℓp Metrics. In IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2023) & Neural Information Processing Systems (NeurIPS) Workshop on Optimization for Machine Learning (OPT 2022).

Paper Poster

Buyun Liang, Tim Mitchell, Ju Sun (2021). NCVX: A User-Friendly and Scalable Package for Nonconvex Optimization in Machine Learning. ArXiv preprint arXiv:2111.13984.

Paper

J. Ilja Siepmann, Jingyi L. Chen, Buyun Liang, Krishnan Mahesh (2020). Effect of Non-Condensable Gas on the Thermophysical Properties of Bubbly Water and on Bubble Collapse Dynamics Probed by Molecular Simulations. 33rd Symposium on Naval Hydrodynamics, Osaka, Japan, 18-23 October 2020.

Paper