In the Design Innovation & Generative InTelligence (DIGIT) Lab, we study and create AI and machine learning methods for engineering design, with the goal of solving the most challenging design problems including high-dimensional problems, inverse design problems, design under uncertainty, and novel design discovery. We work together to build a future where AI augments humans in design tasks in terms of efficiency, creativity, complex reasoning, and trustworthiness.

Through our research, we aim to develop general design tools that can be broadly applied to solving complex design problems in many science and engineering domains, such as aerodynamic design, functional materials design, soft robot design, and design for manufacturing.

For more information, you can explore our paper collection or check out our open-source code.

We are excited to welcome two new members, Haoxuan Mu and Jiahui (Cal) Zheng, to our team!

Posted 16 Aug 2023 by Wei

Wei (Wayne) Chen is awarded the Journal of Mechanical Design 2022 Reviewer Of The Year Award.

Posted 06 Mar 2023 by Wei

Paper on “T-Metaset: Task-Aware Generation of Metamaterial Datasets by Diversity-Based Active Learning” received the DAC Best Paper Award and Paper of Distinction Recognition at the International Design Engineering Technical Conferences (IDETC).

Posted 25 Aug 2022 by Wei
Posted 18 Aug 2022 by Wei