The lab has published over 100 papers, including more than 40 in CAS JCR Q1 or CCF-A venues
Publications appear in top power systems journals: IEEE Transactions on Smart Grid (IF 8.6), IEEE Transactions on Sustainable Energy (IF 8.6), Applied Energy (IF 10.1)
Also published at premier AI conferences: NeurIPS, ICLR, IJCAI
Holds over 10 national invention patents in AI-energy interdisciplinary research
Paper 'LLM-Enhanced Trading Decision Framework with Multi-Scale Memory for Electricity Markets' won Best Paper Award at IEEE SmartGridComm'25 (2025)
Paper 'Socially Aware Load Forecasting Utilizing Large Language Models' accepted by IEEE Transactions on Industrial Informatics (CAS Tier 1, IF 9.9)
Background
Principal Investigator of the Intelligame Lab at University of Electronic Science and Technology of China (UESTC)
Research focuses on the intersection of Artificial Intelligence and Smart Grids
Aims to enhance the efficiency, resilience, and intelligence of future energy systems through data-driven methodologies
Core research areas include machine learning for power systems, intelligent building energy management, power trading, and multi-modal AI applications
Actively contributes to China's national carbon neutrality goals and intelligent urban infrastructure development