Ming Shi

photo_mingshi 

I am a Post-Doctoral Scholar of the Department of Electrical and Computer Engineering and NSF AI-EDGE Institute at The Ohio State University, Columbus, OH, USA. I am fortunate to be advised by Prof. Ness Shroff and Prof. Yingbin Liang.

I received my Ph.D. degree from Elmore Family School of Electrical and Computer Engineering, College of Engineering at Purdue University, West Lafayette, IN, USA, in 2022. I was fortunate to be advised by Prof. Xiaojun Lin.

Email: shi.1796 [at] osu [dot] edu or sming [at] purdue [dot] edu

I will join the Department of Electrical Engineering at the University at Buffalo (SUNY Buffalo) as an assistant professor in fall 2024.

Research interests

    My research strives to develop AI-powered autonomous networked systems with strong theoretical performance guarantees under uncertainty and practical domain-specific constraints.

  • Reinforcement learning, bandit learning, and generative AI

  • Online (non-)convex optimization and online control

  • Networking, wireless communications, cloud computing, cyber-physical systems, SDN/NFV, energy and power systems, transportation, and economics

  • Theoretical performance analysis, e.g., competitive ratio, dynamic and static regret, sample complexity, equilibrium, convergence rate, and value of prediction.

News and Honors

  • Invited talk: “Autonomous Networked Systems: Adversarial Online RL Under Limited Defender Resources”

    - at New York University (NYU), New York, November 2023.

  • Invited talk: “AI-Powered Autonomous Systems with Switching Costs: Power-of-2-Arms”

    - at the Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts, July 2023.

  • Invited talk: “Near-Optimal Adversarial Reinforcement Learning with Switching Costs”

    - at the California Institute of Technology (Caltech), Pasadena, California, July 2023.

  • Invited talk: “RL under Instantaneous Hard Safety Constraints and POMDPs: From Wireless Communications to Smart Health”

    - at Northeastern University (NEU), Boston, Massachusetts, July 2023.

  • Conference presentation: “A Near-Optimal Algorithm for Safe Reinforcement Learning Under Instantaneous Hard Constraints”

    - at International Conference on Machine Learning (ICML), Honolulu, Hawaii, July 2023.

  • Conference presentation: “Near-Optimal Adversarial Reinforcement Learning with Switching Costs”

    - at International Conference on Learning Representations (ICLR), Spotlight presentation, virtual, May 2023.

  • Notable-top-25% (Spotlight) paper, International Conference on Learning Representations (ICLR), January 2023.

  • Conference presentation: “Leveraging Synergies Between AI and Networking to Build Next Generation Edge Networks”

    - at IEEE Conference on Collaboration and Internet Computing (CIC), virtual, December 2022.

  • Conference presentation: “Power-of-2-Arms for Bandit Learning with Switching Costs”

    - at ACM International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing (MobiHoc), Seoul, South Korea, October 2022.

  • Invited talk: “Power-of-2-Arms for Bandit Learning with Switching Costs”

    - at the California Institute of Technology (Caltech), Pasadena, California, May 2022.

  • Conference presentation: “Combining Regularization with Look-Ahead for Competitive Online Convex Optimization”

    - at IEEE Conference on Computer Communications (INFOCOM), virtual, May 2021.

  • Bilsland Dissertation Fellowship, Purdue University, April 2021.

  • IEEE INFOCOM Student Conference Award, US National Science Foundation (NSF), March 2021.

  • Conference presentation: “On the Value of Look-Ahead in Competitive Online Convex Optimization”

    - at ACM SIGMETRICS / IFIP Performance Joint International Conference (SIGMETRICS), Phoenix, Arizona, June 2019.

  • ACM SIGMETRICS Student Travel Grant, US National Science Foundation (NSF), May 2019.

  • Conference presentation: “Competitive Online Convex Optimization with Switching Costs and Ramp Constraints”

    - at IEEE Conference on Computer Communications (INFOCOM), Honolulu, Hawaii, April 2018.

  • IEEE INFOCOM Student Travel Grant, US National Science Foundation (NSF), March 2018.