Dr. Crowley leads innovation and growth at the intersection of health and artificial intelligence across the Federal Health sector. A health informaticist, he delivers cutting-edge solutions that merge health data science, information system design, and responsible AI for his Federal clients.
Before Accenture, he was Managing Director of a Digital Health Research Center of Excellence and Health Insights AI Lab at the University of Maryland, where he led a broad portfolio of R&D programs and partnerships that produced groundbreaking products and scientific findings, and served as faculty in information systems and AI. He continues to teach Responsible AI at the Johns Hopkins University Carey Business School.
Dr. Crowley has envisioned, built, and evaluated AI and digital health solutions from concept through clinical trial, market, and next generation. His work spans federal agencies, startups, Fortune 500 companies, and healthcare providers and payers, and has earned international recognition at premier conferences, including his teams' wins in national health informatics design competitions. He has served as a scientific reviewer for the National Science Foundation and the National Institutes of Health, an advisor on data innovation to the National Committee on Vital and Health Statistics, and a Health XPRIZE mentor. When he's not building AI solutions, you might find him kayaking the Chesapeake, enjoying live music, or spending time with his wife and children.
Education
PhD, Information Studies, University of Maryland at College Park
MBA, University of Maryland at College Park
BSBA, University of North Carolina at Wilmington
Research
Selected Publications
Smolyak, D., Bjarnadóttir, M. V., Crowley, K., & Agarwal, R. (2024). Large language models and synthetic health data: progress and prospects. JAMIA open, 7(4), ooae114.
Gressler, L. E., Crowley, K., Berliner, E., Leroy, H., Krofah, E., Eloff, B., ... & Vythilingam, M. (2023, May). A quantitative framework to identify and prioritize opportunities in biomedical product innovation: a proof-of-concept study. In JAMA health forum (Vol. 4, No. 5, p. e230894).
Agarwal, R., Bjarnadottir, M., Rhue, L., Dugas, M., Crowley, K., Clark, J., & Gao, G. (2023). Addressing algorithmic bias and the perpetuation of health inequities: An AI bias aware framework. Health Policy and Technology, 12(1), 100702.
Crowley, K., Dugas, M., Gao, G., Burn, L., Igumbor, K., Njapha, D., ... & Agarwal, R. (2022). Market segmentation of South African adolescent girls and young women to inform HIV prevention product marketing
Working Papers
Governing agents: Closing the trust gap through agent harness engineering
Teaching
Responsible AI
Honors and Distinctions
2025 ACT-IAC Innovation of the Year; 2023 FORUM Change Agent Award; American Public Health Association Codeathon winner, Scientific reviewer for NSF and NIH
Impact and Engagement
Business
Managing Director, Health AI & Data Lead, Accenture Federal Services
In the Media
Revolutionizing Public Health Surveillance, FedGov Today (11/2023)
4 Keys to Modernizing Public Health Data Collection and Analysis, HIT Consultant Magazine (05/2023)