Our group has received a substantial computational resource allocation through the NSF ACCESS program to study multimodal sensing data in advanced manufacturing processes. Dr. Mojumder’s project will utilize these computational resources to develop a machine-learning model that accurately predicts process fingerprints of advanced manufacturing processes. This research can potentially replace expensive sensors used in the advanced manufacturing process with more affordable alternatives, thanks to the innovative use of multimodal data fusion. The project will span from July 16, 2024, to July 15, 2025, during which the team will conduct code development, profiling, and testing in a high-performance computing environment.