The most important challenges facing society rarely fit within a single discipline. They involve complex data, interconnected systems, uncertain environments, and decisions with real consequences.
At the University of Oklahoma's Data Science and Analytics Institute, researchers from engineering, computer science, health sciences, business, and other disciplines work together to develop the methods and technologies needed to address these challenges. From trustworthy artificial intelligence and advanced machine learning to resilient infrastructure, precision health, climate and weather, and autonomous systems, DSAI combines fundamental data science with domain expertise to create knowledge and solutions with real-world impact.
The Data Science and Analytics Institute (DSAI) is a rapidly growing division of the Gallogly College of Engineering covering four different areas of expertise:
Read more about our different areas of expertise below and see how DSAI fits into your career journey.
280+
Masters graduates
Prepared for Careers in Data Science, Analytics, AI, Research, Biomedical, Technology and expanding!
20+
Employer Partners
And a growing Network of Alumni Working Across Industry, Government, Research, and Higher Education
Artificial intelligence is transforming science, engineering, business, and society. DSAI researchers are advancing the algorithms and systems that make AI more capable and more trustworthy. Our research spans machine learning, deep learning, generative AI, natural language processing, computer vision, reinforcement learning, explainable AI, robust AI, and human-centered artificial intelligence.
The systems that shape our world are rarely simple. Supply chains, transportation networks, critical infrastructure, organizations, markets, and communities are interconnected—and disruptions can propagate across those connections.
DSAI researchers combine artificial intelligence, network science, optimization, simulation, operations research, and analytics to understand complex systems, anticipate risk, improve resilience, and support better decisions.
Expertise includes
Modern biomedical research generates enormous amounts of complex, heterogeneous data—from medical images and electronic health records to genomic, proteomic, and neurological measurements.
DSAI researchers develop computational and AI methods that transform these data into new insights about human health and biological systems. Our interdisciplinary research connects artificial intelligence and data science with medicine, biology, neuroscience, and biomedical engineering.
Oklahoma provides an exceptional environment for research at the intersection of artificial intelligence, weather, climate, water, hazards, and resilient communities. DSAI researchers combine machine learning with physical science, remote sensing, hydrology, geospatial analytics, and scientific computing to improve our understanding and prediction of complex Earth systems.
This work ranges from forecasting and environmental monitoring to flood prediction, natural hazards, infrastructure resilience, and scientific machine learning.
Discover how graduate students at the University of Oklahoma are making a real impact in bleeding-edge technology.
Dr. Bin Leads the Autonomous Driving System Development at OU
At the University of Oklahoma's Mobility Intelligence Lab (MiLa) in OU Aerospace and Mechanical Engineering, Dr. Bin Xu and a team of 7 Ph.D. and dozens of undergraduate researchers are building a prototype autonomous driving system that can retrofit any consumer vehicle for roughly $1,000 in hardware, a sharp contrast to the six-figure cost of Waymo's Jaguar-based robotaxis. The MiLa team starts by hacking into the cars to take over the steering, acceleration and braking controls, fitting consumer vehicles with off-the-shelf cameras, GPS units, computers and sensors that perceive surroundings, plan and follow paths, and navigate to a destination. Its fleet includes three Nissan LEAFs, a Hyundai Ioniq 5,a Dodge Ram cargo van. The retrofitted cars are then used to train the lab's own end-to-end learning algorithms. Their self-driving vehicles are running around OU Norman campus every day and data is then used to retrain the system overnight, producing updated software for the next day. Though only about five years old, it already contributes to three federally funded projects (one from U.S. Department of Transportation and two from U.S. Department of Energy) worth more than $16 million, covering rural and tribal road logistics, public transit for the city of Atoka, autonomous methane leak detection system.
