Emerging manufacturing technologies such as additive manufacturing and micro/nano fabrication allow designs to be fabricated in a much wider spectrum of complexity and scale. This release of design freedom could potentially mean a tremendous improvement in functional capabilities (e.g., aircraft with lower energy consumption, soft robots with more flexible locomotion, solar cells with higher energy conversion efficiency, and magnetic resonance imaging with more accurate diagnosis). The question is: How can we create new design methods that can well adapt to such high design freedom? Dr. Wei (Wayne) Chen will present his work on using machine learning to overcome the high-dimensionality challenge and fully release the freedom in engineering design. By rethinking what should be a good representation of a design space, he treats the design space as a design element and uses artificial intelligence (AI) and machine learning (ML) to automatically learn and explore this space. By doing this, we can solve some of the most challenging design problems such as extremely high-dimensional optimization problems, novel design synthesis, high-throughput inverse design, and design under realistic free-form uncertainty. He will discuss how his works can apply to broad science and engineering domains including aerodynamic design, functional materials design, and design for manufacturing.
About the Speaker
Dr. Wei (Wayne) Chen is a postdoctoral scholar working with Professor Wei Chen in Mechanical Engineering at Northwestern University. Wei received his Ph.D. in Mechanical Engineering in 2019 from the University of Maryland at College Park, advised by Professor Mark Fuge. After graduation, Wei worked as a Research Scientist in the Design & Simulation Systems group at Siemens for 1.5 years. Wei’s research focuses on how artificial intelligence (AI) and machine learning (ML) can assist humans in solving challenging design problems including extremely high-dimensional problems, high-throughput inverse design, design under realistic uncertainty, and novel design synthesis.
Host: Professor Iwona Jasiuk