Artificial Intelligence for Energy Efficiency

Prof. Lee has published 23 SCI papers in the past five years (2019-2023), all related to the application of Artificial Intelligence (AI) in enhancing energy efficiency. These papers have been extensively cited, with an average citation count of 36 for the nine papers where he was the first author. His Field-Weighted Citation Impact (FWCI) is 1.235, and he has achieved an h-index of 20. His latest publication in "Applied Thermal Engineering" focuses on "Artificial Intelligence Enabled Energy-Efficient Heating, Ventilation, and Air Conditioning System: Design, Analysis, and Necessary Hardware Upgrades." This paper details the design methods for improving the energy efficiency of HVAC systems using AI and has already garnered 3 citations within three months of publication. These achievements demonstrate Prof. Lee's unique academic insights in AI for Energy Efficiency.

Beyond academic accomplishments, in the past five years, Prof. Lee has undertaken 46 research projects commissioned by the government and enterprises, totaling 3.1 million USD. Most of these projects relate to the application of AI in energy conservation, including in air conditioning systems, buildings, factories, and even urban public facilities. His extensive experience in industry-academia collaboration enriches his book on AI for Energy Efficiency, providing many practical examples of improved energy efficiency, making the content more comprehensive.

Dr. Jeng is a Senior Principal Researcher at the Green Energy & Environment Research Laboratories in the Industrial Technology Research Institute (ITRI) in Taiwan. He earned his Ph.D. degree in 1992 from National Cheng-Kung University and has been with ITRI since 1993. In 2004, he was a visiting scholar at the Massachusetts Institute of Technology. With over 30 years of experience in energy research, his work spans building energy efficiency, LED lighting, HVAC systems, renewable energy, hydrogen energy, and thermoelectric materials. He has published over 100 articles and holds more than 30 patents in these fields. Currently, Dr. Jeng serves as the Deputy General Director of the Green Energy & Environment Research Laboratories in ITRI, where he oversees research projects in energy efficiency and clean environment.

Dr. Tsai received his Ph.D. in Mechanical Engineering from National Taiwan University, Taiwan, in 2021. He has been focusing on Artificial Intelligence (AI) applications in his recent research. A significant aspect of his work is integrating Reinforcement Learning with a robotic arm model, which allows the robotic arm to execute specific tasks. He presented this research at the 19th International Conference on Automation Technology. Additionally, Dr. Tsai's latest studies involve the use of deep learning for diagnosing eccentricity in permanent magnet synchronous motors and detecting faults in ball bearings.