Seminar: Data-Driven Design of Microstructural Material Systems

Data Science for Materials Discovery

Data-Driven Design of Microstructural Material Systems

Professor Wei Chen
Northwestern University

In this talk, we will introduce the state-of-the-art data science methods for designing heterogeneous nano- and microstructural materials and metamaterial systems such as polymer nanocomposites, light-weight composite structures, functional microelectronics, and solar cells. Research developments in microstructure characterization and reconstruction, machine learning of key microstructure features, and data-driven Bayesian optimization using mixed-variable Gaussian process models, will be described.

Friday, February 19
10-11 am PDT / 11 am MST/ 1 pm EST

https://cuboulder.zoom.us/j/96007553384
Password: i-aim

Abstract:
Design of advanced material systems imposes challenges in integrating knowledge and representation from multiple disciplines and domains such as materials, manufacturing, structural mechanics, and design optimization. Data-driven machine learning and computational design methods provide a seamless integration of predictive materials modeling, manufacturing, and design optimization to enable the accelerated design and deployment of advanced materials systems. In this talk, we will introduce the state-of-the-art data science methods for designing heterogeneous nano- and microstructural materials and metamaterial systems such as polymer nanocomposites, light-weight composite structures, functional microelectronics, and solar cells. Research developments in microstructure characterization and reconstruction, machine learning ​of key microstructure features, and data-driven Bayesian optimization using mixed-variable Gaussian process models, will be introduced. Challenges and opportunities in designing engineered material systems will be discussed.

About the Speaker:
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- http://ideal.mech.northwestern.edu/), her current research involves issues such as simulation-based design under uncertainty; model validation and uncertainty quantification; data science in design and advanced manufacturing; stochastic multiscale analysis and materials design; design of metamaterials; multidisciplinary design optimization; consumer choice modeling and decision-based design.  She is a member of the National Academy of Engineering (NAE) and currently serving as the Editor-in-chief of the ASME Journal of Mechanical Design and the President of the International Society of Structural and Multidisciplinary Design (ISSMO). Dr. Chen was the recipient of the 2015 ASME Design Automation Award and 1996 NSF Faculty Career Award.  She received her Ph.D. from the Georgia Institute of Technology in 1995.