MRI: Acquisition of Artificial Intelligence & Deep Learning (AIDL) Training and Research Laboratory

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Researchers in health, biomedical science, and various engineering fields often do not receive sufficient training in using the most powerful approach to machine learning known to date, an approach called "deep learning", for analying their data. Deep learning is based on simulated artificial neural networks, and for large real-world problems requires access to specialized computer hardward and software. Such hardware and software platforms, however, are rarely part of the information technology resources available for researchers outside of the field of computer science. This project will overcome this barrier by procurement and development of a deep learning platform at Florida Atlantic University for such research. The project provides a training hub for industry and university to work closely on advanced artificial intelligence applications, and in turn might benefit economic growth.This infrastructure project supports creation of a deep learning platform for health, biomedicine, ocean research, and related domains at Florida Atlantic University. The platform will be shared across campus to service multiple domains. The project brings about a centralized cross campus interdisciplinary platform and augmented deep learning and related artificial intelligence tools for interdisciplinary research. The former, jointly managed by the College of Engineering and Computer Science, and the FAU office of Information Technology, enables building upon the experience and frameworks of others that eventually results in shared infrastructure savings. The latter is likely to contribute in building/augmenting AI and DL tool kits for interdisciplinary research, including augmentation of existing common machine learning and deep learning algorithms for domain experts to carry out analysis on their data without requiring intensive programming skills. Augmented AI and DL tools should be particularly useful to ocean engineers and health sciences.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.