Our research lies at the intersection of data management and AI, with three integrated thrusts: (1) enabling the reusability of AI models by developing principled storage, indexing, and metadata techniques that make pretrained models easily discoverable, composable, and adaptable across tasks with provable performance guarantees; (2) advancing responsible structured and vectorized data management through the collection, storage, processing, and governance of data to ensure accuracy, trustworthiness, ethical integrity, and compliance with legal and societal expectations; and (3) designing scalable, human-in-the-loop decision-support systems for national security, leveraging and adapting Generative AI and applied machine learning technologies for predictive maintenance and cyber defense, engineered to operate under stringent performance, security, and resource constraints while delivering trustworthy, mission-critical intelligence.

The research projects at BDAL are funded by the National Science Foundation, Office of Naval Research, National Institute of Health, Microsoft Research, Multicare Health Systems.