Biography
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 for machine and deep learning, robustness in vision recognition and AI for science and engineering. Specifically, I am interested in: 1). User-friendly and scalable software for constrained optimization in deep learning; 2). Adversarial robustness in computer vision; 3). AI for topology optimization; 4). Learning from unbalanced biomedical data.
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 for Deep Learning
- Robustness in Vision Recognition
- AI for Science & Engineering
M.S. in Computer Science, 2020 - Present
University of Minnesota, Minneapolis, MN, USA πΊπΈ
M.S. in Materials Science, 2018 - 2020
University of Minnesota, Minneapolis, MN, USA πΊπΈ
B.S. in Physics, 2014 - 2018
Nanjing University, Nanjing, Jiangsu, China π¨π³
Recent News
[Nov 26, 2022] To be a Reviewer for 2023 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2023).
[Nov 10, 2022] Our tutorial proposal Deep Learning with Nontrivial Constraints has been accepted to SIAM International Conference on Data Mining (SDM23) Tutorial Program as a two-hour tutorial!
[Oct 20, 2022] Our paper NCVX: A General-Purpose Optimization Solver for Constrained Machine and Deep Learning has been accepted by Neural Information Processing Systems (NeurIPS) Workshop on Optimization for Machine Learning (OPT 2022), see our poster for more details!
[Oct 20, 2022] Our paper Optimization for Robustness Evaluation beyond βp Metrics has been accepted by Neural Information Processing Systems (NeurIPS) Workshop on Optimization for Machine Learning (OPT 2022), see our poster for more details!
[Oct 03, 2022] Proud to release our paper NCVX: A General-Purpose Optimization Solver for Constrained Machine and Deep Learning on arXiv! This is an expanded version of our previous announcement paper, with four detailed examples on constrained deep learning.
[Oct 03, 2022] Proud to release our paper Optimization for Robustness Evaluation beyond βp Metrics on arXiv! This is a preview of our ongoing project that numerically solves adversarial attack problems with general metrics (vs SOTA that only deals with β1, β2, and ββ), taking advantage of our NCVX framework.
[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!
Publications
Website ICCOPT22 Slides SDM2023 Tutorial ICASSP 2023 Tutorial
Software
Powerlifting
Fall 2022 Mock Competition
Body Weight: 77.1kg. Squat: 163.3kg; Bench Press: 115.7kg; Deadlift: 192.8kg. Total 471.7kg.
Summer 2022 Mock Competition
Body Weight: 77.3kg. Squat: 154.2kg; Bench Press: 113.4kg; Deadlift: 188.2kg. Total 455.9kg.
2022 USA Powerlifting Minnesota Junior, Open & Master State Championships
Body Weight: 76.35kg. Squat: 157.5kg; Bench Press: 105kg; Deadlift: 180kg. Total 442.5kg.
2018 Raise the Bar – Powerlifting
Body Weight: 75.3kg. Squat: 165.6kg; Bench Press: 102.1kg; Deadlift: 172.4kg. Total 440kg.
2018 Han Tang Powerlifting (ζ±εζ―第εε±ε€§ιε₯εηΊͺε½θ΅)
Body Weight: 73.6kg. Squat: 160kg; Bench Press: 95kg; Deadlift: 170kg. Total 425kg.
