Keynote Speaker I
Biography: Maria Pia Fanti received the Laurea degree in electronic engineering from the University of Pisa, Pisa, Italy. She was a visiting researcher at the Rensselaer Polytechnic Institute of Troy, New York, in 1999. Since 1983, she has been with the Department of Electrical and Information Engineering of the Polytechnic University of Bari, Italy, where she is currently a Full Professor of system and control engineering and Chair of the Laboratory of Automation and Control. Her research interests include management and modeling of complex systems, such as transportation, logistics and manufacturing systems; discrete event systems; Petri nets; consensus protocols; fault detection. Prof. Fanti is IEEE fellow and has published more than 320 papers and two textbooks on her research topics.
She was senior editor of the IEEE Trans. on Automation Science and Engineering and she is Associate Editor of the IEEE Trans. on Systems, Man, and Cybernetics: Systems. She was member at large of the Board of Governors of the IEEE Systems, Man, and Cybernetics Society, and currently she is member of the AdCom of the IEEE Robotics and Automaton Society, and chair of the Technical Committee on Automation in Logistics of the IEEE Robotics and Automation Society. Prof. Fanti was General Chair of the 2011 IEEE Conference on Automation Science and Engineering, the 2017 IEEE International Conference on Service Operations and logistics, and Informatics and the 2019 IEEE Systems, Man, and Cybernetics Conference.
Keynote Speaker II
Speech Title：Artificial Intelligence (AI) Modeling of PEM Fuel Cell
Biography: Yun Wang received his B.S. and M.S. degrees in Mechanics and Engineering Science from Peking University in 1998 and 2001, respectively. He went to the Pennsylvania State University where he earned his Ph.D degree in Mechanical Engineering in 2006. Dr. Wang joined the MAE (Mechanical and Aerospace Engineering) faculty at the University of California, Irvine in 2006. He has produced over 100 publications in PEM fuel cell, Li-air battery, and other energy systems, including three books on PEM Fuel Cell and a Practical Handbook of Thermal Fluid Science. Dr. Wang served as Track chair/co-chair, session chair/co-chair, conference chair and committee member for many international conferences on fuel cell, thermal energy, and machine learning. Dr. Wang received 2018 Reviewer of The Year from the Journal of Electrochemical Energy Conversion and Storage and is currently Professor at the UC Irvine, ASME fellow, RSC fellow, and associate editor for the journal of heat and mass transfer.
Abstract: Polymer electrolyte membrane (PEM) fuel cells are electrochemical devices that can directly convert the chemical energy stored in hydrogen into electrical energy with a peak conversion efficiency as high as 65%. They are regarded as a promising power source for portable, transportation and stationary applications. In this talk, I will present the technological status, fundamentals including the multiphysics and electrochemical processes, and artificial intelligence models for PEM fuel cells. Several examples of AI models for PEM fuel cell R&D, including AI material design for porous medial flow field, operational condition optimization, and neutron radiography AI analysis for in-situ liquid water monitoring, will be explained in detail.