Shaolei Ren

Shaolei Ren Associate Professor of Electrical and Computer Engineering Cooperating Faculty of Computer Science and Engineering University of California, Riverside

News and Selected Papers

• I have multiple openings available for graduate students (with full financial support) and visiting scholars. Potential research projects include, but are not limited to: intelligent systems, machine learning, etc. Students can apply to the PhD program in either ECE or CSE department at UCR. Prior experiences are not required. Please contact me if you're interested.
  

• Learning and optimization

  • Robust learning for optimization

    • Learning for competitive online convex optimization: SIGMETRICS’22, INFOCOM’23

  • Learning for robust optimization: INFOCOM’22

  • Learning-assisted online algorithm unrolling: AAAI’23

  • Knowledge-informed and continual learning: ICML’22, NeurIPS’22

• Ultra-efficient ML for edge inference

  • Brain-inspired low-dimensional computing classifiers: tinyML’22

    • It offers overwhelming advantages over state-of-the-art HDC classifiers: equal (or even higher) accuracy, improved or comparable robustness, orders-of-magnitude smaller model size and bettter inference efficiency (latency and energy).

  • Scalable neural architecture search: SIGMETRICS’22 (Webpage, GitHub)

    • Given N devices, our OneProxy approach can keep the total search cost at O(1).

• Computers, and warehouse-scale computers (a.k.a. data centers)

  • Security: SIGMETRICS’18, SIGMETRICS’20 (video), CCS’17, CCS’18 (video), HPCA’21

  • Power efficiency: HPCA’15, HPCA’16, HPCA’18

  • Demand response: INFOCOM’15, Performance’15, e-Energy’16

Projects

• Towards user-centric deep neural network model selection for edge/IoT devices (funded by the NSF)

• Online learning-assisted resource management in edge computing systems (funded by the NSF)

• Coordinated power management in multi-tenant colocation data centers (funded by the NSF CAREER Award)

• An integrated approach to optimizating energy management in microgrids with large computing loads (completed, funded by the NSF)

• Making cloud computing less “thirsty”! (completed, funded by the NSF)
  
  

Contact

Shaolei Ren
Department of Electrical and Computer Engineering
University of California, Riverside

Office: Winston Chung Hall 319
Phone: 951-827-2260
E-mail: sren (AT) ece.ucr.edu