Plenary Lecture 4

Room: Audimax
Time: Tuesday, 29. September 2026, 9:40 - 10:20
Chair: Jianbing Chen

Lori Graham-Brady

Professor of civil and systems engineering, Whiting School of Engineering,
Director of the JHU Center on AI for Materials in Extreme Environments (CAIMEE)
Johns Hopkins University, Maryland, USA

Data-driven approaches to materials design and multi-scale computational mechanics

Data-driven approaches are transforming how materials are designed, characterized, and optimized. This talk will describe how machine learning is getting integrated into the workflow of a high-throughput experimental environment, with a focus on the AI for Materials Design Laboratory (AIMD-L) at Johns Hopkins University. By coupling experimental data streams with physics-informed and data-driven models, these tools enable rapid, informed, uncertainty-aware decision-making, accelerating the identification of promising compositions and processing pathways for new materials. The talk will also highlight how machine learning supports multi-scale modeling in computational mechanics, linking microscale structure and behavior to macroscale performance. Together, these approaches form a unified framework in which experiments, simulations, and data-driven models work in concert to guide materials design and improve performance in complex engineering systems.

Short Bio

Lori Graham-Brady is a Professor and former Chair of the Civil and Systems Engineering Department at Johns Hopkins University, with secondary appointments in Mechanical Engineering and Materials Science & Engineering. Her research interests are in AI for materials design, computational stochastic mechanics, multiscale modeling of materials with random microstructure and the mechanics of failure under high-rate loading. She is the Director of the Center on AI for Materials in Extreme Environments and previous Director of both an NSF-funded IGERT training program with the theme of Modeling Complex Systems, and the Center for Materials in Extreme Dynamic Environments. She has received several awards, including the Presidential Early Career Awards for Scientists and Engineers (PECASE), the Walter L. Huber Civil Engineering Research Prize, and the William H. Huggins Award for Excellence in Teaching.