MRI: Acquisition of a Cyberinstrument for AI-Enabled Computational Science & Engineering

This project aims to acquire an instrument focusing on Artificial Intelligence to drive fundamental research and enable applications of existing methodologies. The instrumentation extends the supercomputer at the institution and would serve as catalysts for academic partnerships in the state among Clemson, Medical University of S.C. (MUSC), USC, and some HBCUs.

The Instrument extends the supercomputer at the institution and enables research on: Artificial Intelligence, Machine Learning, Computational Intelligence, Deep Learning, and Statistical Methods. The instrument enables research on Biomedical Data Science and Informatics, including the development of tools and deep learning methods for third generation sequencing data, new machine-learning algorithms for biomedical knowledge discovery systems. The Instrument enables research on root nodulation in legumes, cancer biology, and genomics algorithms; Visual Computing. It also enables research on fundamental problems related to physical simulation and numerical control problems spanning broadly from predictive scientific visualization to production of artificial sampling data for Deep Neural Network Training and to the control and safety assurance of real-world artifacts such as autonomous vehicles.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.