CODE2 Lab

News

Lab updates

Announcements, publications, recognition, and opportunities from the CODE2 Lab.

Dr. Wang presented her work, “Autonomous Materials Characterization through Continual Deep Learning with Simulated and Experimental Materials Data,” at ASME IDETC-CIE. In this work, she explored how uncertainty-aware learning, simulation-to-experiment adaptation, and continual learning can help enable more reliable and adaptive materials characterization for autonomous scientific discovery.

Dr. Zihan Wang presenting at ASME IDETC-CIE
Conference presentation at ASME IDETC-CIE.
Group photo from ASME IDETC-CIE
ASME IDETC-CIE gathering with colleagues.

The CODE2 Lab website is live. We are recruiting fully funded Ph.D. students for 2026/2027 admission in AI for materials, engineering design, and scientific machine learning. View openings

The ARCO-BO paper on collaborative Bayesian optimization for heterogeneous multi-agent design appears in the Journal of Mechanical Design. View publications

Zihan Wang received the ASME Design Automation Dissertation Award and was selected for the MIT Rising Stars in Mechanical Engineering workshop.