Faculty and research staff at the University of Alabama in Huntsville, Alabama A & M University, and Tuskegee University conduct research in a wide variety of Critical Technology areas including artificial intelligence, machine learning, data visualization, modeling and simulation, and big data analytics. Listed below are highlights of a few ongoing research efforts demonstrating the breadth and depth of our research.

Text Mining/Visualization. Faculty members in Computer Science and researchers in the Information Technology and Systems Center (ITSC) have developed the Spyglass ontological text mining application to help MSIC and other intelligence agencies index, search, and access millions of documents on specific topics. Spyglass captures semantic information and contextual knowledge of analysts. The system provides multiple visualizations that show the distribution of documents across categories and relationships between documents/categories.

Modeling and Simulation. UAH Computer Science faculty and ITSC researchers have decades of experience in Modeling and Simulation (M&S) research and development. They have completed projects for sponsors that include the Missile and Space Intelligence Center, the Missile Defense Agency, the U. S. Air Force, the U. S. Army, and the Defense Advanced Research Projects Agency. Selected M&S projects performed by ITSC researchers include the development of human behavior models for computer controlled opponents in battlefield simulation (artificial intelligence); the application of reinforcement learning and digital pheromones to anticipate future attacks by Somali pirate attacks in the Gulf of Aden and the western Indian Ocean (machine learning); an analysis of the effectiveness of simulation-based training without instructor participation (data visualization); and the development of algorithms for efficient data distribution in networked simulation systems (algorithm design).

Machine Learning and Hyperspectral Imagery. Dr. Joel Fu and other researchers at Alabama A & M University are using machine learning and Artificial Color to develop advanced methods for spectral segmentation and spatial analysis of hyperspectral images. The measured HSC (hyperspectral camera) image data are projected onto two or three convex, overlapping, broad curves in analogy with the sensitivity curves of human cone cells. Using POCS (Projections onto convex sets) on the HSC data researchers are able to reduce the processing complexity to produce excellent discrimination.

Computer Vision with Radio Frequency Identification Devices (RFID). The Computer Science Department at Tuskegee University has several ongoing Data Science related projects including RFID/IoT data cleansing, intrusion detection and bioinformatics. Researchers are working on data cleansing of indoor tracking and monitoring RFID data and scoring cancer cells using computer vision and machine learning. TU researchers also are integrating Data Science into cyber security, including topics in intrusion detection, deep learning, cloud-deployed applications, and clustering.