Jones Seminar: Integrating Physical Intelligence with Artificial Intelligence—Autonomous design and manufacturing of emerging material systems

ZOOM LINK
Meeting ID: 935 8655 7757
Passcode: 008066

Achieving superior performance in future material systems hinges on optimizing the heterogeneity of materials and structures. However, the design and fabrication of such advanced systems present significant challenges, requiring the integration of knowledge across multiple domains—including materials science, manufacturing, structural mechanics, and design optimization.

This talk introduces a paradigm shift toward unifying "physical intelligence" with artificial intelligence (AI) to realize "embodied intelligence" in material systems. By combining data-driven generative design with physics-based modeling and simulation, we enable seamless integration of predictive materials modeling, advanced manufacturing, and design optimization—accelerating the development and deployment of next-generation materials. We will present state-of-the-art design methodologies that leverage statistical inference and AI techniques for the design of nano- and micro-structured materials and programmable metamaterials responsive to external stimuli, covering methods such as machine learning, mixed-variable Latent Variable Gaussian Process (LVGP) modeling, Bayesian optimization, differentiable simulation, topology optimization, and generative design. The talk will also highlight recent advances in digital twins for autonomous co-design and manufacturing, using additive manufacturing as an example to showcase how these tools are transforming the landscape of intelligent material systems.

Hosted by Professor Yan Li.

About the Speaker(s)

Wei Chen
Wilson-Cook Professor in Engineering Design, Northwestern U

Wei Chen is the Wilson-Cook Professor in Engineering Design and Chair of Department of Mechanical Engineering at Northwestern University. Directing the Integrated DEsign Automation Laboratory (IDEAL), her current research involves the use of statistical inference, AI, and uncertainty quantification techniques for design of emerging materials systems including microstructural materials, metamaterials and programmable materials. She serves as the design thrust lead for the NSF Engineering Research Center (ERC) on Hybrid Autonomous Manufacturing, Moving from Evolution to Revolution (HAMMER), where she works on digital twin systems for concurrent materials and manufacturing process design. A member of the National Academy of Engineering and American Academy of Arts and Sciences, Chen received her PhD in mechanical engineering from the Georgia Institute of Technology and her MS in mechanical engineering from the University of Huston.

Contact

For more information, contact Amos Johnson at amos.l.johnson@dartmouth.edu.