About me
I am a phd candidate in Electrical and Computer Engineering Department at University of California, Riverside, advised by Prof. Shaolei Ren. Before joining UCR, I received my master degree from Beijing University of Posts and Communications supervised by Prof. Lin Sang, and bachelor degree from Xidian University. Also, I worked as a research intern in Tencent AI Lab during spring of 2022, mentored by Dr. Jianshu Chen.
My research lies in machine learning and optimization, as well as their applications in computing systems including edge computing, carbon intelligent computing and energy systems. My recent research focuses are
Trustworthy Machine Learning for Decision Processes
- ML for online optimization and control. SIGMETRICS’22 INFOCOM’23
- ML for online allocation. AAAI’23 ICML’23
- Bandits with context uncertainty. INFOCOM’21 AAAI’21 IJCAI’20
- ML for robust combinatorial optimization. INFOCOM’22
Optimization for Learning with Domain Knowledge
- Doamin Knowledge informed learning. ICML’22
- Efficient Hardware-aware NAS. SIGMETRICS’22
News
Apr 24, 2023 Our paper Learning for Edge-Weighted Online Bipartite Matching with Robustness Guarantees got accepted by ICML 2023!
Apr 10, 2023 Check our new study Making AI Less “Thirsty”: Uncovering and Addressing the Secret Water Footprint of AI Models about water usage of large AI models! Hope this study can remind people of saving the water that AI models are consuming.
Feb 15, 2023 I gave a talk on Intelligent Online Decision-making with Provable Trustworthiness Guarantee in ITA workshop at San Diego. Nice discussions!
Dec 01, 2022 Our paper Robustified Learning for Online Optimization with Memory Costs got accepted by INFOCOM 2023!
Nov 18, 2022 Our paper Learning-Assisted Algorithm Unrolling for Online Optimization with Inventory Constraints got accepted by AAAI 2023!
Jun 30, 2022 I am a receipant of the 2022 UCR Dissertation Year Program (DYP) Award.
May 15, 2022 Our theoretical work Informed Learning by Wide Neural Networks: Convergence, Generalization and Sampling Complexity got accepted by ICML 2022.
Mar 28, 2022 Our paper Expert-Calibrated Learning for Online Optimization with Switching Costs got accepted by SIGMETRICS 2022.