MAE Department - PG Seminar - Geometry-Driven Intelligence: Reshaping Manufacturing through AI-Driven Design and Process Planning
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The future of manufacturing lies in bridging geometric computing, computational physics, and artificial intelligence. This talk explores how these domains can be integrated to reshape the design-to-production pipeline - enabling systems that are not only functional but also fabrication-aware, adaptive, and optimized. I will present recent advances in robot-assisted vector 3D printing, where toolpaths are aligned with structural needs and process constraints; neural representations that support co-optimization of geometry, material orientation, and toolpath generation; and closed-loop planning frameworks that adapt deposition strategies in real-time based on force sensing and process feedback. These developments enable the co-evolution of form, material, and process, resulting in printed parts with enhanced performance, reduced porosity, and higher structural integrity.
Professor Charlie C.L. Wang is internationally recognized for his research in geometry-driven intelligence for design and manufacturing, where he has established geometric computing and optimization as foundational mechanisms for intelligent engineering solutions. His work has transformed the integration of design, analysis, and fabrication by embedding manufacturability, material behaviour, and process constraints directly into geometric design variables, enabling adaptive, high-performance manufacturing systems across additive and hybrid processes. He is currently Chair Professor of Smart Manufacturing at the University of Manchester (UoM) holding an EPSRC Fellowship (2023-2028) on Field Computation Based Kernel for Vector 3D Printing. Before joining UoM in 2020, he worked as Professor and Chair of Advanced Manufacturing at Delft University of Technology and as Professor of Mechanical and Automation Engineering at the Chinese University of Hong Kong. He received his B.Eng. of Mechatronics Engineering from Huazhong University of Science and Technology (1998) and his Ph.D. of Mechanical Engineering from Hong Kong University of Science and Technology (2002). Prof. Wang has received numerous recognitions, including the ASME CIE Excellence in Research Award (2016), ten Best Paper Awards, five project-oriented awards, and three teaching awards. He is Fellow of the American Society of Mechanical Engineers (ASME) and the Solid Modelling Association (SMA).