Ming Yi

Ming Yi

Postdoctoral Research Scientist at Columbia University

Postdoctoral Research Scientist
Data Science Insititute
Columbia University, New York City

Office: CEPSR 801
Address: Schapiro Center, 530 W 120th St Suite 1001, New York, NY 10027
Email: my2826@columbia.edu

About Me

I am a postdoctoral research scientist at Columbia University, where I am focusing on energy storage, the power market, and the resilience of power systems. I am fortunate to work with Prof. Bolun Xu and Prof. Gil Zussman. Before that, I worked as a postdoc fellow at the University of Michigan, Ann Arbor, for three months with Prof. Parth Vaishnav, Prof. Michael Craig, Prof. Johanna Mathieu, and Prof. Carina Gronlund. I obtained my Ph.D. degree in 2022 from the Department of Electrical, Computer, and Systems Engineering at Rensselaer Polytechnic Institute, where I am fortunate to be advised by Prof. Meng Wang. In Spring 2022, I interned at the Argonne National Laboratory, mentored by Dr. Dongbo Zhao and Dr. Tianqi Hong. I received a Master’s degree in Control Science and Engineering from Harbin Institute of Technology and a Bachelor’s degree in Automation from Harbin Engineering University in 2018 and 2016, respectively.

I am broadly interested in (1) designing data-driven algorithms to enhance intelligence, sustainability, and resilience in energy systems, (2) integrating renewable energy, energy storage, and emerging decarbonization technologies, and (3) modeling the impacts of climate change on energy systems.

I am on the academic job market this fall! Feel free to reach out if you’re interested in my research or have relevant opportunities.

Please see my CV if you want to know more about me.

[CV] [Research Statement] [Teaching Statement]

Highlights

  • [Mar. 2025] Our paper entitled “Perturbed Decision-Focused Learning for Modeling Strategic Energy Storage “ was accepted in IEEE Transactions on Smart Grid.
  • [Feb. 2025] Our paper entitled “Conformal Uncertainty Quantification of Electricity Price Predictions for Risk-Averse Storage Arbitrage” was accepted in IEEE PES General Meeting 2025.
  • [Sept. 2023] Our paper entitled “Energy Storage Arbitrage in Two-settlement Markets: A Transformer-Based Approach” was accepted in Electric Power Systems Research.
  • [July 2023] I am honored to receive the Columbia University Data Science Institute Postdoctoral Fellowship, which supports next-generation of leaders in data science and artificial intelligence.
  • [May 2023] Our paper entitled “Net Load Forecasting with Disaggregated Behind-the-Meter PV Generation” was accepted in IEEE Transactions on Industry Applications.
  • [April 2023] I am honored to receive the Charles M. Close ’62 Doctoral Prize from the ECSE department of Rensselaer Polytechnic Institute. This prize is awarded to a doctoral candidate who has done outstanding work as a researcher and teacher, and who shows promise of a distinguished academic or research career.
  • [Mar. 2023] Our paper entitled “Bayesian High Rank Hankel Matrix Completion for Nonlinear Synchrophasor Data Recovery” was accepted in IEEE Transactions on Power Systems.
  • [Oct. 2022] I am honored to receive the Founders Award of Excellence (top 1% of student population) from Rensselaer Polytechnic Institute.
  • [May 2022] Our paper entitled “Recent Results of Energy Disaggregation with Behind-the-Meter Solar Generation” was accepted in 11th Bulk Power Systems Dynamic and Control Symposium.
  • [Feb. 2022] Our paper entitled “Bayesian Robust Hankel Matrix Completion with Uncertainty Modeling for Synchrophasor Data Recovery” was accepted in ACM SIGENERGY Energy Informatics Review.
  • [Jun. 2021] Our paper entitled “Bayesian Energy Disaggregation at Substations with Uncertainty Modeling” was accepted in IEEE Transactions on Power Systems.
  • [Nov. 2020] Our paper entitled “Real-time Energy Disaggregation at Substations with Behind-the-Meter Solar Generation” was accepted in IEEE Transactions on Power Systems.

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