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About Me

He is an associate professor at the school of electrical engineering in Southeast University, Nanjing, China. He is the member of the group by Prof. Zaijun Wu and Prof. Qinran Hu. He recieved Ph.d degree, majoring in electrical engineering, from Tsinghua University and is part of Energy Management System (EMS) group head by Prof. Hongbin Sun. He was a visiting scholar in UC, Berkeley, advised by Prof. Shmuel S. Oren. He received the B.S and M.S degree from Southeast University, Nanjing, China with honors in 2018, 2021 respectively. He is also a research intern on LLM for power systems supervised by Dr. Wotao Yin in Decision Intelligence Lab, DAMO Academy, Alibaba.

He is working on fusing artificial intelligence and operation research for sustainable power system analytics from prediction, to scheduling, to controling. CV

Recent News

[Dec. 2025] Our paper “Data-driven Hybrid Power Flow Model in Distribution Networks: A Tree-based Approach” was accepted to CSEE Journal of Power and Energy Systems;

[Aug. 2025] Our paper “RIS-Assisted Communications: A Comprehensive Study for Far- and Near-Field Scenarios” was accepted to IEEE Transactions on Cognitive Communications and Networking;

[Aug. 2025] I am glad to annouce that I have been promoted to Associate Professor in Southeast University;

[Jul. 2025] Our paper recieved the recipient of the 2025 IEEE PES Prize Paper Award;

Selected Papers

• L. Sang, Y. Xu, H. Sun, Z. Wu, Q. Wu, and W. Wu, “Distribution Locational Marginal Emission for Carbon Alleviation in Distribution Networks: Formulation, Calculation, and Implication”, IEEE Transactions on Automation Science and Engineering, Early Access, 2025.
• L. Sang, Y. Xu, W. Wu, and H. Long, “Online Voltage Regulation of Active Distribution Networks: A Deep Neural Encoding-Decoding Approach, ” IEEE Transactions on Power Systems, Early Access, 2023.
• L. Sang, Y. Xu, and H. Sun, “Encoding Carbon Emission Flow in Energy Management: A Compact Constraint Learning Approach, ” IEEE Transactions on Sustainable Energy, Early Access, 2023. Arxiv
• L. Sang, Y. Xu, Z. Yi, H. Long, and H. Sun, “Conservative Sparse Neural Network Embedded Frequency Constrained Unit Commitment With Distributed Energy Resources,” IEEE Transactions on Sustainable Energy, Early Access, 2023. Arxiv
• L. Sang, Y. Xu, and H. Sun, “Ensemble Provably Robust Learn-to-optimize Approach for Security-Constrained Unit Commitment, ” IEEE Transactions on Power Systems, Early Access, 2022.
• L. Sang, Y. Xu, H. Long, and W. Wu, “Safety-aware Semi-end-to-end Coordinated Decision Model for Voltage Regulation in Active Distribution Network, ” IEEE Transactions on Smart Grid, Early Access, 2022. Arxiv
• L. Sang, Y. Xu, H. Long, Q. Hu, and H. Sun, “Electricity Price Prediction for Energy Storage System Arbitrage: A Decision-focused Approach,” IEEE Transactions on Smart Grid, vol. 13, no. 4, pp. 2822-2832, July 2022. Arxiv
• L. Sang, Q. Hu, Y. Xu, and Z. Wu, “Privacy-preserving Hybrid Cloud Framework for Real-time TCL-based Demand Response,” IEEE Transactions on Cloud Computing, Early Access, 2022.
• H. Long, L. Sang, Z. Wu, and W. Gu, “Image-Based Abnormal Data Detection and Cleaning Algorithm via Wind Power Curve,” IEEE Transactions on Sustainable Energy, vol. 11, no. 2, pp. 938-946, Apr. 2020. Arxiv

Full publication list could refer to Google scholar，Researchgate .