• Associate Professor, Computer Science & Engineering
Yi Zhou

Educational Background

  • Ph.D., Electrical and Computer Engineering, The Ohio State University – 2018
  • B.S., Electrical Engineering, Beijing Institute of Technology – 2013

Research Interests

    • Nonconvex and distributed optimization
    • Reinforcement learning
    • Statistical learning theory
    • Machine learning (ML) for exploratory data analysis (EDA) and computer-aided design (CAD)

Awards & Honors

  • Air Force Research Laboratory Visiting Faculty Research Program – 2024
  • Faculty Early CAREER Award, National Science Foundation Electrical, Communications and Cyber Systems – 2023
  • Spotlight paper award, NeurIPS – 2018

Selected Publications

  • Zhou, Y., et al. “Boosting one-point derivative-free online optimization via residual feedback,” in IEEE Transactions on Automatic Control (TAC), 2024.
  • Zhou, Y., et al. “On the hardness of constrained cooperative multi-agent reinforcement learning,” in Proc. International Conference on Learning Representations, 2024.
  • Zhou, Y., et al. “On the hardness of online nonconvex optimization with single oracle feedback,” in Proc. International Conference on Learning Representations, 2024.
  • Zhou, Y., et al. “A resource-efficient task scheduling system using reinforcement learning,” in Proc. Asia and South Pacific Design Automation Conference (ASP-DAC), 2024, pp. 89–95.
  • Zhou, Y., et al. “Assisted learning for organizations with limited imbalanced data,” Transactions on Machine Learning Research (TMLR), 2023.