Dr Mingyang Sun is a Professor (Research) at Peking University. Also, he is an Honorary Lecturer at Imperial College London, UK. He received his Ph.D. degree in Electrical and Electronic Engineering in the Control and Power (CAP) group at Imperial College London in 2017. From 2017 to 2019, he was a Research Associate and a DSI Affiliate Fellow at Imperial College London. After that, he was a Professor (Research) at the Department of Control Science and Engineering, Zhejiang University.His research mainly focuses on the investigation of novel Big Data Analytics and Artificial Intelligence methods for low-carbon energy systems, with a special emphasis on dealing with uncertainties arising from RES and energy consumers for system investment planning and operation. In particular, his research interests include data-driven cyber-physical energy system operation and control, smart meter data analysis, energy forecasting, flexibility quantification, and large-scale energy system investment planning. He has authored more than 80 scientific publications in Nature Communications and leading power system journals, and top AI and security conferences, including IEEE PES Transactions, Applied Energy, AAAI, IJCAI, USENIX Security, and NDSS with 3 ESI highly cited papers. Four of our papers have been awarded the Best Papers for IEEE TSG 2023, IEEE PES GM 2016, PMAPS 2016, and IEEE TrustCom 2022, respectively. Also, he has been awarded as one of the World’s Top 2% Scientists released by Stanford University. Furthermore, our paper has been awarded the Highly Cited Paper Awards 2019 of Applied Energy. He is currently the Associate Editor, Leading Guest Editor, and Guest Editor of a series of international journals, including IEEE Transactions on Industrial Informatics, Applied Energy, Advances in Applied Energy, and IET Smart Grid, etc. Furthermore, he is the PI/CO-PI for a series of key projects funded by the NSFC, National Key R&D Program of China, The Royal Society （UK）, and China Association for Science and Technology. Furthermore, he was involved in many multi-partner collaborative projects and led the work regarding machine learning for trial data modelling and analysis. The projects concerned were “EU-SysFlex” (Horizon 2020, EUR20 million), “Innovative Tools for Electrical System Security within Large Areas (iTesla)”, (FP7, EUR19.4 million), and “Low Carbon London” (UK Power Networks, GBP28 million).