Students on Summer Project Team:
Ryan Forelli '24, Computer Engineering
Alibek Kaliyev '24, CSB
Tri Nguyen '21, Materials Science & Engineering
FJ Olugbodi '23, Computer Engineering
William Reichard-Flynn 'G, Earth & Environmental Science
Andrew Zheng '24, Mechanical Engineering

Faculty Mentor(s): Joshua Agar, Assistant Professor, Materials Science & Engineering

Project Video: Click here to view

Project description:
In materials science and physics more broadly there is a growing trend to conduct multimodal experiments (experiments that collect data from a variety of sources). The boon in data collection has left a majority of the data collected under-analyzed leaving important physics left undiscovered. This project developed machine and deep learning methods to discover actionable information from such data. This project also considered how such models can be implemented on specialty AI hardware for real-time analysis. The work focused on materials problems as they provide unique ways to stress-test practical theories of machine and deep learning. Outcomes of this work have direct impacts on creating interpretable AI, controlling fairness and bias, and creating autonomous control systems. The impacts of these theories can be adapted to solve problems in medicine and healthcare, resource management and logistics, and manufacturing and processing.