Prof. Yangquan Chen
University of California, USA

YangQuan Chen earned his Ph.D. from Nanyang Technological University, Singapore, in 1998. He had been a faculty of Electrical Engineering at Utah State University (USU) from 2000-12. He joined the School of Engineering, University of California, Merced (UCM) in summer 2012 teaching “Mechatronics”, “Engineering Service Learning”, “Unmanned Aerial Systems” and “Digital Twins” for undergraduates; “Fractional Order Mechanics”, “Linear Multivariable Control”, “Nonlinear Controls” and “Advanced Controls: Optimality and Robustness” for graduates. His research interests include mechatronics for sustainability, cognitive process control and smart control engineering enabled by digital twins, small multi-UAV based cooperative multi-spectral “personal remote sensing”, applied fractional calculus in controls, modeling and complex signal processing, distributed measurement and control of distributed parameter systems with mobile actuator and sensor networks. He is listed in Highly Cited Researchers by Clarivate Analytics from 2018 to 2021. He received Research of the Year awards from USU (12) and UCM (20). Most recently he started with Dr. Bruce J. West a new book series of CRC Press on AFC4STEM (Fractional Order Thinking in Exploring the Frontiers of STEM) and established a new section for Fractals and Fractional journal on “Optimization, big data and AI/ML”. His Google Scholar citations are over 55100 with H-index 100, H-10 index 643.

Prof. Jiehan Zhou, University of Oulu, Finland

Jiehan Zhou is a Docent (Associate Professor) in Network Information Systems at University of Oulu. He received his 2nd PhD in Network Information Systems from University of Oulu and 1st PhD in Manufacturing and Automation from Huazhong University of Science and Technology. He has worked as a Post-Doc in Tsinghua University, VTT/Oulu, INRIA/Sophia-Antipolis (ERCIM Fellow),CRP Henri Tudor/Luxembourg, University of Tortonto,Carleton University, and Professor/Lecturer in Algonquin College. He has published more than 130 peer-reviewed journal, book chapter, and conference papers in Network Information Systems and Intelligent Manufacturing Systems. He has been granted more than one million Euro project funding, supervised and participanted more than 15 projects (more than 100 million) in China, Finland, and Canada. He has given more than 10 lectures in computer and automation. He serves in many international journals , conferences and workshops. He is visiting profs in China University of Petroleum, Qingdao and Wuhan University of Science and Technology and research fellow in Carleton University and University of Toronto, Canada.

Prof. Hongfa Hu

University of Windsor, Canada

Dr. Hongfa (Henry) Hu is a tenured full Professor at Department of Mechanical, Automotive & Materials Engineering, University of Windsor. He was a senior research engineer at Ryobi Die Casting (USA), and a Chief Metallurgist at Meridian Technologies, and a Research Scientist at Institute of Magnesium Technology.
He received degrees from University of Toronto (Ph.D., 1996), University of Windsor (M.A.Sc., 1991), and Shanghai University of Technology (B.A.Sc., 1985). He was a NSERC Industrial Research Fellow (1995-1997). His publications (over 230 papers) are in the area of magnesium alloys, composites, metal casting, computer modelling, and physical metallurgy. He was a Key Reader of the Board of Review of Metallurgical and Materials Transactions, a Committee Member of the Grant Evaluation Group for Natural Sciences and Engineering Research Council of Canada, National Science Foundation (USA) and Canadian Metallurgical Quarterly. He has served as a member or chairman of various committees for CIM-METSOC, AFS, and USCAR. He was one of 2022 & 2023 World’s Top 2% Scientists (Stanford/Elsevier).
The applicant’s current research is on materials processing and evaluation of light alloys and composites. His recent fundamental research is focussed on transport phenomena and mechanisms of solidification, phase transformation and dissolution kinetics. His applied research has included development of magnesium automotive applications, cost-effective casting processes for novel composites, and control systems for casting processes. His work on light alloys and composites has attracted the attention of several automotive companies.

Title: Light Weighing Battery-Powered Electric Vehicles
Abstract. Battery-powered electric vehicles (BEV) have become popular on the auto market. However, BEVs are in generally heavier than gasoline-powered vehicles due to the presence of massive batteries. Weight reduction is essential to the BEV industry. The substitution of castable light aluminum alloys with superior strengths and electrical conductivity for copper can reduce the weight and size of electric induction motors, and improve the energy efficiency and driving range of the BEVs. The presentation will provide a general introduction into the common wrought and cast Al aluminum alloys and their relevant processes, and to motivate the development of inexpensive high strength and conductive Al alloys for practical realization of Al applications in the motors of the BEVs. A number of cast alloy systems containing Cu, Si, Ni, Mg, Fe and Ti will be evaluated, in comparison to nanostructured wrought Al alloys. The conventional casting processes suitable for Al alloys, high pressure die casting, squeeze casting and sand casting, will be described. Strengthening mechanisms including solid solution strengthening, precipitation strengthening, dislocation accumulation strengthening and grain boundary strengthening will be presented. The phenomenon of electrical conduction for Al alloys will be outlined. The mechanical properties and electrical properties of the recently developed Al alloys for casting and deformation processes will be comprehensively listed and critically reviewed in association with microstructural characteristics.