Trustworthy and physics-informed AI
Learning methods with physical consistency, interpretability, adversarial robustness, uncertainty awareness and verifiable performance.
Professor of Electrical Engineering
Trustworthy AI and decision intelligence for resilient renewable-rich energy systems
I develop physics-informed, privacy-preserving and verifiable learning, robust optimisation, and safe multi-agent decision methods for cyber-physical power and energy systems.
210Scopus-indexed documents
10,148Scopus citations
50Scopus h-index
25ESI Highly Cited Papers
39IEEE Transactions papers
Research metrics updated September 2026.
Profile
International research leadership across power systems and trustworthy intelligence
Yang Li is a Professor and Ph.D. Supervisor at Northeast Electric Power University. His research connects power-system fundamentals with trustworthy artificial intelligence, optimisation and control to improve the security, resilience and decarbonisation of modern energy infrastructure.
He was a postdoctoral researcher at Argonne National Laboratory from 2017 to 2019. He has been named a Clarivate Highly Cited Researcher in Engineering in both 2024 and 2025 and serves in international editorial and IEEE leadership roles.
Research
Four connected research themes
Cyber-physical energy-system resilience
Detection, defence, recovery and resilient operation under false-data injection, coordinated attacks, missing data and cascading disruptions.
Robust optimisation and decision intelligence
Stochastic, robust and distributionally robust optimisation for renewable-rich microgrids, integrated energy systems and flexible demand.
Federated learning and safe multi-agent RL
Privacy-preserving collaborative intelligence and safe sequential decision-making for networked resources and multi-energy systems.
Application domains: renewable integration, smart grids, microgrids, distributed energy resources, storage, electric vehicles, demand response, forecasting, system security and stability.
Selected publications
Recent and representative work
- 2026QSTAformer: A quantum-enhanced Transformer for robust short-term voltage stability assessment against adversarial attacks.
Applied Energy, 405, 127196. - 2026ZTFed-MAS2S: A zero-trust federated learning framework with verifiable privacy and trust-aware aggregation for wind power data imputation.
IEEE Transactions on Industrial Informatics, 22(1), 165–175. - 2026A physics-informed graph convolution network for AC optimal power flow via refining DC solution.
IEEE Transactions on Power Systems, 41(1), 438–453. - 2025Safe-AutoSAC: AutoML-enhanced safe deep reinforcement learning for integrated energy system scheduling.
Applied Energy, 399, 126468. - 2023Data-driven distributionally robust scheduling of community integrated energy systems with uncertain renewable generations considering integrated demand response.
Applied Energy, 335, 120749. - 2022Detection of false data injection attacks in smart grid: A secure federated deep learning approach.
IEEE Transactions on Smart Grid, 13(6), 4862–4872.
Leadership and service
Editorial and professional leadership
IEEE leadership
- Chair, IEEE PES Energy Internet Coordinating Committee Task Force on AI-Enabled Resilience of Cyber-Physical Energy Systems
- Founding Chair, IEEE Systems Council Harbin Section Chapter
IEEE journals
- Associate Editor, IEEE Transactions on Smart Grid
- IEEE Transactions on Sustainable Energy
- IEEE Transactions on Industrial Informatics
- IEEE Transactions on Industry Applications
- IEEE Power Engineering Letters
Energy journals
- Section Chief Editor, Energy Reports
- Young Editorial Board Member, Applied Energy
- Lead Guest Editor, Applied Energy VSI on AI-enabled resilience
- More than 3,600 completed peer reviews
Recognition
Selected honours
- 2025Clarivate Highly Cited Researcher
Engineering - 2024Clarivate Highly Cited Researcher
Engineering - 2022–2024Elsevier Highly Cited Chinese Researcher
Electrical Engineering - 2022–2025World’s Top 2% Scientist
Stanford/Elsevier ranking - 2020State Council Special Government Allowance
China
Recipient of five provincial Science and Technology Progress Awards, including two First-Class and two Second-Class awards.
Research programmes
Selected programmes
Royal Society International Exchanges
China-side Lead / Co-Applicant; federated deep reinforcement learning for resilient multi-microgrids.
National Natural Science Foundation of China
Core team member; identification and adaptive defence against cyber-physical coordinated attacks.
National Key R&D Programme of China
Key participant; power-meteorological monitoring, intelligent forecasting and demonstration applications.
Utility-engaged research
Principal-investigator and project-lead work with State Grid, NARI and Beijing Kedong.
People and education
Graduate supervision and teaching
Teaching portfolio
Power-system analysis, electrical systems of power plants, renewable integration, optimisation, intelligent scheduling, cyber-physical security, professional English, academic writing and research integrity.
Contact
Research and academic enquiries
School of Electrical Engineering
Northeast Electric Power University
Jilin, China