Through IDSC, the University is developing an AI testbed that gives scientists access to state-of-the-art AI/ML tools and a dedicated high-performance computing infrastructure, incorporating human experts in the loop for developing, evaluating, and addressing the most challenging AI/ML application problems.

	Artificial Intelligence in Biomedical Imaging Research has found that AI tools perform better than doctors in some radiology imaging tasks. We believe that AI tools will expedite time-consuming diagnosis processes and improve accuracy in diagnosis for benefits of the patients. Read more
	AI/NLP for EHR Analytics In clinical domains, various types of free texts appear including generic clinical text, discharge summary, insurance claims, clinical notes, lab reports, radiology reports, pathology reports, and clinical trial reports. We can extract information from such text data using natural language processing (NLP) tools and deep learning. Read more
	FDA AI Testbed The overall goal of this project is to develop an infrastructure platform that will facilitate continuous testing and monitoring of diagnostic AI devices operating at real-world clinical practice sites. The platform will also enable data collection for real-world performance evaluation of AI/ML-enabled, computer-aided, detection/characterization/triaging (CAD) devices in radiology and health care applications in clinical practices. Read more
	NIH AIM-AHEAD Program Our investigators are a part of an AIM-AHEAD infrastructure core that will enable a coordinated data and computing infrastructure that enhances the interoperability of large-scale data resources with data that are maintained, governed, and prepared by individual institutions to preserve privacy and autonomy. Below are some of the innovation tools which we are working on building for the program. Read more
	AI/ML for Marine Atmospheric Boundary Layer profiles via Satellite Remote Sensing Data Fusion The Planetary Boundary Layer (PBL) is the layer of atmosphere bordering the surface of the earth and represents the greatest importance to human activities.  It is also the most difficult layer of the atmosphere to measure directly. Read more
	Intelligently Secured Distributed Solution To make their analytical service reliable, the distributed machine learning solutions must secure inter-device data transmission from several cyber threats such as jamming, eavesdropping, denial of service, and so on. However, data transmission among the distributed, densely deployed machine learning agents are more vulnerable, compared to the traditional communication equipment, to cyber-attacks for the following reasons. Read more
	Networking with Humans in the Loop Next-generation networks such as the Internet of Things (IoT), connected and autonomous vehicles (CAVs), social networks, augmented and virtual reality (AR/VR), as well as other wireless connected systems are expected to have enhanced capacity to autonomously process data and operate. However, such intelligent systems still need to work under human intervention, and act fast enough to the irrational and psychological behaviors. The goal of this research direction is to introduce novel networking solutions and enable intelligent devices quickly interpret and response to complex human behavior. Read more