Announcement Detail


Large Scale Structural Systems and Optimal Design Industrial Colloquium

Wednesday, June 18, 2025

1:00 PM CDT

Join via Zoom: https://us06web.zoom.us/j/87331120699?pwd=MExkQ085ZHh1aDc3ZnBwQzFlUHI4UT09

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Large Scale Structural Systems and Optimal Design Virtual Seminar

The Shape of Intelligence: Designing Smart Materials to Cloak, Morph, and Move

Speaker

Assistant Professor Liwei Wang, Carnegie Mellon University

Abstract

Robots and machines often rely on chips and electronics to perform complex sensing, actuation, and control tasks. Recent advances in manufacturing have made it possible to embed intelligent functions directly into materials and structures, giving rise to chip-free physical intelligence. This emerging paradigm allows engineered materials to autonomously adapt and move in response to mechanical loading, external stimuli, or environmental changes, offering transformative potential across biomedical, environmental, and robotics applications. This flexibility, however, introduces significant challenges in inverse design, where designers must navigate complex physical behavior and vast high dimensional design spaces. In this talk, we will explore how computational intelligence, including machine learning and computational optimization, can be harnessed to establish inverse design principles and methods to program the materials behaviors for physical intelligence. The first part of the talk focuses on the co-design of materials and structures in heterogeneous metamaterials. We will present a framework that integrates deep generative modeling with multiscale optimization to design unfeelability cloaks that conceal objects from mechanical detection. The second part discusses how differentiable simulation and topology optimization can be combined to co-design materials, structures, stimuli, and even manufacturing processes. This integrated approach enables efficient programming of various responsive behaviors in material systems, ranging from shape morphing under heat, light, and magnetic fields to the dynamic locomotion of untethered soft robots.

Bio

Liwei Wang is an Assistant Professor of Mechanical Engineering at Carnegie Mellon University, where he directs the Computational and Physical Intelligence Laboratory (CPhI Lab). His lab develops computational design frameworks for advanced material systems with enhanced physical intelligence. Liwei’s research combines machine learning algorithms, mechanics models, and multi-physics optimization methods for 3D/4D printing, smart structures, metamaterials, and multifunctional, programmable materials. His research group is exploring applications that can enhance human well-being and extend human capabilities, such as mechanical protective cloaks, minimally invasive surgery, soft robotics, and mechanical computing.
Before joining Carnegie Mellon University, Liwei was a postdoctoral scholar (2022–2024) and a visiting scholar (2019–2021) in the Department of Mechanical Engineering at Northwestern University. He earned his B.S. and Ph.D. in Mechanical Engineering from Shanghai Jiao Tong University. His work has been recognized with the inaugural ASME Design Automation Dissertation Award, the university-level Outstanding Ph.D. Dissertation Award, and a Best Paper Award at the ASME Design Automation Conference.