Thomas Ciardi
LinkedIn
Education:
B.A. in Computer Science & Cognitive Science, CWRU
Current PhD Student in Computer & Data Sciences, CWRU
Research Areas: Deep Learning, 2-4D Segmentation (XCT, AFM, SEM Imaging), st-GNN, Computing Infrastructure
Thesis Topic: Deep Learning Framework for the Spatiotemporal Graph Representation of Terabyte-scale 4D XCT Datasets
Hometown: New Fairfield, CT
Background: My research sits at the intersection of machine learning and materials science. I am fundamentally interested in 1) how models work, 2) their extension to real-world problems, 3) frameworks to translate Tera/Petabyte scale datasets into digestible representations, and 4) interpretability mechanisms that enable scientific understanding in model decisions. I focus on the adaptation of vision-based deep learning, spatiotemporal GNNs, and generative models to materials science challenges and modalities: XCT of AlMg SCC, FKM crystallization growth kinetics, LPBF defect detection, PV power forecasting. I also contribute to our group’s computing and data infrastructure, designing APIs to make high performance and distributed computing accessible to researchers.
