Speakers

Prof. Yang Yue

School of Information and Communication Engineering/Xi’an Jiaotong University, China 

Experience: Prof. Yang Yue received the B.S. and M.S. degrees in electrical engineering and optics from Nankai University, China, in 2004 and 2007, respectively. He received the Ph.D. degree in electrical engineering from the University of Southern California, USA, in 2012. He is a Professor with the School of Information and Communications Engineering, Xi'an Jiaotong University, China. Dr. Yue’s current research interest is intelligent photonics, including optical communications, optical perception, and optical chip. He has published over 200 journal papers (including Science) and conference proceedings with >10,000 citations, five edited books, two book chapters, >50 issued or pending patents, >200 invited presentations (including 2 tutorial, >40 plenary and >50 keynote talks). Dr. Yue is a Senior Member of IEEE, Optica and SPIE. He is an Associate Editor for IEEE Access and Frontiers in Physics, Editor Board Member for four other scientific journals, Guest Editor for >10 journal special issues. He also served as Chair or Committee Member for >100 international conferences, Reviewer for >70 prestigious journals.

Prof. Shengrong Bu

Department of Engineering, Brock University, Ontario, Canada

Title: AI-Driven Decarbonization for Energy Systems

Abstract: The ongoing decarbonization of energy systems is currently altering the fundamental structure of system operation and planning by increasing the penetration of renewable energy resources (RESs), while forecasting an increase in the asset utilization of high electrification of transportation and efficient heating facilities. To meet the carbon budgets, the pace of decarbonization in energy systems with deregulating markets needs to be significantly accelerated. These transitions, however, present crucial techno-economic challenges for energy systems. More flexibilities are required to balance the less predictable and controllable outputs of RESs. A large number of small-scale distributed energy resources (DERs) are located and operated in a distributed manner, which may increase the challenges of managing them. Finally, privacy concerns also need to be addressed due to the massive amount of data communicated by the decentralized energy systems. In this context, this talk will focus on several kinds of approaches for energy systems decarbonization, and how state-of-the-art reinforcement learning and AI tools could be applied to address challenges.

Experience: 

Professor Shengrong Bu received her Ph.D. degree in Electrical and Computer Engineering from Carleton University, Canada in 2012. From 2012 to 2014, she held a research position at Huawei Technologies Canada Inc., Ottawa, as an NSERC Industrial R&D Fellow. From 2014 to 2021, she was a Lecturer with the James Watt School of Engineering, University of Glasgow, UK. Currently, she is an Associate Professor at Brock University, Canada. Her research interests include multi-energy microgrids, smart grids, future wireless networks, cyber security, deep reinforcement learning, and big data analytics. Dr. Bu was a recipient of three best paper awards at IEEE International conferences. Her work has been supported by EPSRC(UK) and NSERC (Canada). Highlights of her professional activities include duties as a peer reviewer for EPSRC and Carnegie Trust, an Associate Editor for Wireless Networks (Springer), a Topic Editor for Energies and the TPC Co-Chair for seven international conferences/workshops or conference symposiums.

Professor Shengrong Bu was featured in the Women in Energy Transformation Series 2022-2024, as one of Canada’s most inspiring climate leaders. Promoting engineering to younger girls and supporting junior female researchers are a passion of hers, and she has been involved with Ontario Go Eng Girl in Canada, Monster Confidence in UK, and N2Women as a Mentoring Co-Chair.

Prof. Shijie Jia

School of Computer and Communication Engineering, Dalian Jiaotong University, China

Research Area: Image processing and pattern recognition, machine learning theory and technology.

Research Experience: Prof. Shijie Jia, male, PhD in Engineering, professor and vice president of School of Computer and Communication Engineering, Dalian Jiaotong University, member of Expert Committee of China Simulation Technology Industry Alliance, member of China Communication Society; mainly engaged in research and teaching of image processing and pattern recognition, machine learning theory and technology. He has published more than 50 academic papers in important academic journals and international conferences, among which more than 30 have been included in the three major search engines, published one academic monograph, authorized 7 invention patents, and won the Dalian excellent IT teacher award, the second prize of natural science and technology achievements of Liaoning Province.