Activities and Awards
Awards and Honors
Red Bird Academic Advisor, HKUST, 2022
Best Paper on Renewables, Storage, & Electric Vehicles, PES General Meeting 2022, State-of-Charge Aware EV Charging
Highlight Paper, Power Systems Computation Conference (PSCC) 2020, Data-Driven Optimal Voltage Regulation using Input Convex Neural Networks
Best Paper Runner-Up, ACM e-Energy 2019, Exploiting Vulnerabilities of Load Forecasting through Adversarial Attacks
Clean Energy Institute Fellowship, University of Washington, 2017
Chu Kochen Overseas Fellowship, Zhejiang University, 2016
Professional Activities
Session Chair, “Recent Advancements of Data-driven Decision Making in Energy Systems”, INFORMS 2022
Guest associate editor, IET Renewable Power Generation
Special Issue Editor, Frontiers in Communications and Networks
Special Issue Editor, Frontiers in Energy Research
Technical Program Committee, SmartGridComm 2020 and SmartGridComm 2022
Reviewer for IEEE Transactions on Power Systems, IEEE Transactions on Smart Grids, IEEE Transactions on Sustainable Energy, IEEE Transactions on Control of Network Systems, IEEE Transactions on Cloud Computing, IEEE Transactions on Industrial Informatics, INFORMS Journal on Computing, Applied Energy, Scientific Reports, Energy Reports, IEEE Transactions on Artificial Intelligence, IEEE Transactions on Neural Networks and Learning Systems
Conference reviewer for American Control Conference, Conference on Decision and Control, SmartGridComm, Power Systems Computation Conference (PSCC), Neurips, PES General Meeting
Invited Talks
Learning to Optimize the Carbon Emissions: a System Perspective, Invited talk at Workshop of Learning and control for decarbonized energy and transportation systems, IEEE Conference for Decision and Control. December 2023
Learning to Optimize: From Charging an EV to Dispatching Gigawatts Renewables, Zhejiang University, Hangzhou, China. April 2023
Learning to Make Decisions with Engineering Constraints: From Electric Vehicles to Power Networks, Shanghai Jiaotong University, Shanghai, China. November 2022
Learning to Charge Electric Vehicles: Modeling and Decision-Making, Hong Kong University of Science and Technology, Hong Kong SAR October 2022
ML for Power Systems: En-Route to Sustainability, University of California San Diego, San Diego, CA June 2022
Enabling Safe Decision Making in Clean Energy Systems, UC Berkeley & Lawrence Berkeley National Laboratory, Berkeley, CA December 2021
State-of-Charge-Aware EV Charging, INFORMS Annual Meeting, Anaheim, CA October 2021
Learning Generalizable Network Flow Solver via Neural Networks, INFORMS Annual Meeting,Washington D.C. November 2020
Learning To Solve Optimal Power Flow via Robust Neural Decoding, INFORMS Annual Meeting, Washington D.C. November 2020
Enabling Optimal Decision Making via Machine Learning, College of Control Science and Engineering, Zhejiang University, Hangzhou, China. July 2020
Exploiting Vulnerabilities of Load Forecasting, INFORMS Annual Meeting, Seattle,WA. October 2019
Optimal Control via Neural Networks, Invited Talk at Symposium of Controlling Complex Networks: When Control Theory Meets Network Science, NetSci 2019, Burlington, VM. June 2019
Renewable Scenario Generation Using Adversarial Networks, INFORMS Annual Meeting, Phoenix, AZ. November 2018
Optimal Control via Neural Networks, Invited Talk at Center for Nonlinear Studies, Los Alamos National Laboratory, Los Alamos, NM August 2018
Model-Free Scenario Generations for Renewables, 2nd Physics Informed Machine Learning (PIML), Santa Fe, NM. January 2018
Disease Diagnosis using Symbolic Regression, Invited Talk, Channing Network Science Seminar at Harvard Medical School, Cambridge, MA January 2016