Trustworthy and physics-informed AI
Learning methods with physical consistency, interpretability, adversarial robustness, uncertainty awareness and verifiable performance.
Full Professor of Electrical Engineering
Trustworthy Decision Intelligence for Resilient Cyber-Physical Energy Systems
Full Professor, NEEPU | Chair, IEEE PES EICC Task Force | IEEE PES Representative to IEEE Systems Council | IEEE SysC Distinguished Lecturer (2027–2029) | Clarivate Highly Cited Researcher | Trustworthy AI & Resilient CPES
I develop physics-informed, privacy-preserving and verifiable learning, robust optimisation, and safe multi-agent decision methods for renewable-rich power and integrated energy systems.
213Scopus-indexed documents
10,408Scopus citations
50Scopus h-index
36Papers recognised as ESI Highly Cited Papers or Hot Papers (cumulative)
40IEEE Transactions papers
Scopus: 24 October 2026 (citations from 7,954 documents). ESI: cumulative recognition through the 23 September 2026 update. IEEE Transactions total: October 2026.
Google Scholar, 24 October 2026: 13,185 citations · h-index 56 · i10-index 148.
Profile
International research leadership across power systems and trustworthy intelligence
Yang Li is a Full Professor and Ph.D. Supervisor at Northeast Electric Power University. His research focuses on trustworthy decision intelligence for resilient cyber-physical energy systems, connecting power-system fundamentals with trustworthy artificial intelligence, optimisation and control.
He chairs the IEEE PES EICC Task Force on AI-Enabled Resilience of Cyber-Physical Energy Systems, serves as IEEE PES Secondary Representative to the IEEE Systems Council, and has been selected as an IEEE Systems Council Distinguished Lecturer for the 2027–2029 term. He was named a Clarivate Highly Cited Researcher in Engineering in 2024 and 2025.
He was a postdoctoral researcher at Argonne National Laboratory from 2017 to 2019 and serves in international editorial 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
- 2027Economic feedback-guided forecasting and scheduling for microgrids using rolling model predictive control.
Applied Energy, 427, 128778 (2027 issue; available online). DOI: 10.1016/j.apenergy.2026.128778. - 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. - 2025Enhancing cyber-resilience in integrated energy system scheduling with demand response using deep reinforcement learning.
Applied Energy, 379, 124831. - 2022Detection of false data injection attacks in smart grid: A secure federated deep learning approach.
IEEE Transactions on Smart Grid, 13(6), 4862–4872. - 2021Coordinating flexible demand response and renewable uncertainties for scheduling of community integrated energy systems with an electric vehicle charging station: A bi-level approach.
IEEE Transactions on Sustainable Energy, 12(4), 2321–2331.
Leadership and service
Editorial and professional leadership
IEEE leadership
- Chair, IEEE PES Energy Internet Coordinating Committee (EICC) Task Force on AI-Enabled Resilience of Cyber-Physical Energy Systems
- IEEE PES Secondary Representative to the IEEE Systems Council
- Selected as IEEE Systems Council Distinguished Lecturer for the 2027–2029 term
- Founding Chair, IEEE Systems Council Harbin Section Chapter
IEEE journals
- Associate Editor, IEEE Transactions on Smart Grid
- Associate Editor, IEEE Transactions on Sustainable Energy
- Associate Editor, IEEE Transactions on Industrial Informatics
- Associate Editor, IEEE Transactions on Industry Applications
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 - 2022–2025Elsevier 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 (two First-Class, two Second-Class and one Third-Class).
Named inventor or co-inventor on 21 granted invention patents (October 2026).
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 education leadership
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.
Student achievements: Students supervised by Professor Li include 11 recipients of China’s National Scholarship for Graduate Students and 3 recipients of the Jilin Province Outstanding Master’s Thesis Award.
International curriculum leadership
Independently designed and taught Power Plant Electrical Systems in English for Samarkand International University of Technology (SIUT), with full academic responsibility for the course. SIUT formally confirmed that the course grades are included in its official academic records and count towards programme requirements and academic credits.
Course delivery and credit recognition confirmed by SIUT, October 2026.
Contact
Research and academic enquiries
School of Electrical Engineering
Northeast Electric Power University
Jilin, China