2024.11.04 ENTEC, NSTDA, Hosts Dr. Hao Wang from Monash University, Australia for Lecture on AI and Optimization in Energy Transition

On November 4, 2024, at Meeting Room M506, National Metal and Materials Technology Center

National Energy Technology Center (ENTEC) welcomed Dr. Hao Wang, a distinguished scholar and ARC DECRA Fellow (2023-2025) from the Department of Data Science and AI, Faculty of IT, Monash University, Australia. Dr. Wang delivered a special lecture on “Optimization and AI for Energy Transition – Energy System Planning, Operation and Management,” highlighting cutting-edge approaches to energy system transformation and discussed potential research collaborations in energy transition.

The visit commenced with a warm welcome from the ENTEC executive team, led by Dr. Lily Eurwilaichitr, Assistant Executive Director, and Dr. Pimpa Limthongkul, Director of Energy Innovation Research Group. The engaging lecture drew significant interest, attracting over 20 ENTEC researchers and staff members who participated in dynamic discussions and knowledge exchange sessions.

Following the lecture, Dr. Pimpa, along with Dr. Kampanart Silva and Mr. Pidpong Janta from the Renewable Energy and Energy Efficiency Research Team, Low Carbon Energy Research Group, engaged in a productive meeting and research experience sharing. Their discussions centered on potential research synergies and collaborative opportunities, laying the groundwork for future joint collaborations.

About Dr.Hao Wang: Dr. Wang currently holds the position of Senior Lecturer (ARC DECRA Fellow 2023-2025) in the Department of Data Science and AI at Monash University, Australia. He previously served as Deputy Theme Lead for IT for Sustainable Energy at Monash University during 2021-2022.
Dr. Wang has led numerous research projects and brings extensive research experience from Stanford University in machine learning for demand response, energy disaggregation, and consumer behavior analysis. His expertise also includes reinforcement learning and online learning for energy storage scheduling and electric vehicle charging from the University of Washington, USA.