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Yan Wang is a Professor of Mechanical Engineering and leads the Multiscale Systems Engineering Research Group at the Georgia Institute of Technology. The research of the group is at the intersection of design, manufacturing, and materials. His research interests include computer-aided design (CAD), computer-aided manufacturing, multiscale modeling and simulation, uncertainty quantification, physics-informed machine learning, and quantum scientific computing. He has published over 100 archived journal papers and over 100 peer-reviewed conference papers, including the ones with best conference paper awards at the American Society of Mechanical Engineers (ASME) Computers & Information in Engineering (CIE) Conference, ASME Multibody Systems, Nonlinear Dynamics, and Control Conference, The Minerals, Metals & Materials Society (TMS) World Congress on Integrated Computational Materials Engineering, the Institute of Industrial & Systems Engineers (IISE) Industrial Engineering Research Conference, and the International CAD Conference. He is a recipient of the U.S. National Science Foundation (NSF) CAREER Award, a National Aeronautics and Space Administration (NASA) Faculty Fellow, and an ASME Fellow. He currently serves on the ASME leadership teams of Digitalization and Intelligent Manufacturing Technology Groups and was the Chair of ASME CIE Division and the Chair of ASME Advanced Modeling & Simulation Technical Committee. He has been frequently invited to give lectures and seminars at universities in U.S., Europe, and Asia, as well as to review proposals for NSF, NASA, Natural Sciences and Engineering Research Council of Canada, European Research Council, German Research Foundation, Singapore Agency for Science, Technology and Research (A*STAR), and Hong Kong Nano and Advanced Materials Institute. He is the Editor-in-Chief of the ASME Journal of Computing & Information Science in Engineering. He also served as the guest editor for Journal of Mechanical Design, Journal of Computational & Nonlinear Dynamics, Journal of Risk & Uncertainty in Engineering Systems, and Computer-Aided Design. Professor Wang received his B.S. degree from Tsinghua University, M.S. from Chinese Academy of Sciences, and Ph.D. from the University of Pittsburgh. His academic career started as a co-Principal Investigator to establish the NSF Industry-University Cooperative Research Center for e-Design in 2003 involving five major U.S. universities and dozens of major U.S. manufacturers. As the Center's information infrastructure research thrust lead, he worked on research issues of product lifecycle management and collaborative engineering including interoperability, persistent naming, and cybersecurity in manufacturing, as well as semantic tolerancing and quantified constraint satisfaction problem to enhance design and manufacturing intelligence. In 2007, he initiated a pioneering research area, computer-aided nano-design, which is to develop new models and descriptions of complex and porous structures at multiple length scales and enable integrated product-materials engineering. Novel modeling concepts such as periodic surface modeling and surfacelets were developed. Periodic surface modeling has now been widely adopted by thousands of engineers and researchers worldwide in modeling porous structures such as additively manufactured scaffolds, metamaterials, and heat exchangers. His recent work includes hybrid physics-based data-driven approaches such as scalable Bayesian optimization, physics-informed machine learning, and physics-based compressive sensing for materials and process design under uncertainty, manufacturing process monitoring, and trustworthy cyber-physical-social systems. Concurrently, he is also devoted to develop new mathematical formalisms and computational methods to enable quantum scientific computing, reliable simulation, and quantitative risk perception modeling. Short Biographical SketchLong Curriculum Vitae |
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