DIGIT Lab
In the Design Innovation & Generative Intelligence (DIGIT) Lab, we study how AI can design better materials, structures, and machines. Our research focus extends beyond model performance and efficiency, exploring how AI can fundamentally advance design across four key dimensions:
- Complexity: How can AI unlock design complexities that are fundamentally inaccessible to traditional methods?
- Trustworthiness: How can we develop AI-driven design methodologies that engineers can trust?
- Discoverability: How can AI discover new knowledge that expands human understanding and guides design innovation?
- Creativity: How can AI enable or accelerate the discovery of “out-of-the-box” design solutions and become a true inventor?
Guided by these fundamental questions, we develop computational methodologies for design ideation, generative design, and design for X (“X” can represent manufacturing, sustainability, reliability, and beyond) across diverse engineering domains.
Latest News
Our paper “GUST: Quantifying Free-Form Geometric Uncertainty of Metamaterials Using Small Data” has been accepted by the Journal of Mechanical Design. More information can be found in Publications.
Our lab is thrilled to announce the successful completion of the TAMUQ Summer Research Internship Program and the Summer Research Experience for Undergraduates Program for 2024. This year, we had the pleasure of hosting two outstanding undergraduate students, Ms. Wisam Gadam and Mr. Eddie Guerrero, who have significantly contributed to our research endeavors. Wisam has been working on Prior-Data Fitted Networks (PFNs) and their application to generative inverse design, while Eddie focused on predicting material properties of metamaterials for manufacturing uncertainty quantification applications.
