Biography
Farzin Ahmadi is an Assistant Professor of Healthcare Management in the College of Health Professions at Towson University, with courtesy appointments at the Johns Hopkins Center for Systems Science & Engineering and the Johns Hopkins Data Science and AI Institute. His research develops AI-driven decision-support systems for complex operational problems, with applications across healthcare management and public policy.
Working at the intersection of operations research, machine learning, and optimization, he builds methods and tools that help managers and policymakers make better decisions under uncertainty. A central thread of his work is inverse optimization — recovering the objectives and preferences that explain observed decisions — which he has applied to personalized nutrition, radiation-therapy treatment planning, and surgical scheduling. His research has been published in leading medical journals, including JAMA and The Lancet Infectious Diseases, and is under review at premier operations venues such as Operations Research, the European Journal of Operational Research, and the INFORMS Journal on Optimization.
Ahmadi is the creator of the Johns Hopkins U.S. Measles Tracker, a county-level surveillance system that provides timely case data and visualizations during the ongoing U.S. measles outbreak. Published as a research letter in JAMA (2025), the tracker has been featured in The Atlantic, CIDRAP, HuffPost, and the JAMA Editor's Summary, and was even referenced as a Jeopardy! clue. Earlier, during the COVID-19 pandemic, he contributed to the globally recognized Johns Hopkins COVID-19 Dashboard, coordinating with state health organizations to maintain timely and accurate county- and state-level data.
He earned his Ph.D. in Civil and Systems Engineering (with an M.S. in Systems Engineering) from Johns Hopkins University, advised by Kimia Ghobadi, and was a Ph.D. researcher at MIT's Computer Science & Artificial Intelligence Laboratory (CSAIL). He subsequently held a postdoctoral fellowship at the Johns Hopkins Center for Systems Science & Engineering. He holds an M.Eng. in Transportation Engineering and a B.Sc. in Civil Engineering from Sharif University of Technology in Tehran, where he graduated in the top 20% of his class and was recognized as a “Brilliant Talented Student” by Iran's National Elites Foundation.
At Towson, Ahmadi teaches courses on the U.S. health system and health information management, and he actively contributes to the operations research community — serving as President of the Johns Hopkins INFORMS Student Chapter, an editorial board member of OR/MS Tomorrow, a peer reviewer for PLOS Global Public Health, and a session and mini-track chair at INFORMS, HICSS, and POMS conferences. He was selected for the HICSS 59 Junior Faculty Consortium in 2026.
Research Focus
Ahmadi's research asks how data and optimization can make operational and clinical decisions measurably better. His current work spans three connected areas:
Inverse optimization and preference learning. Developing theory and methods — including identifiability, statistical inference, and confidence regions — for learning objectives from observed decisions, with applications to personalized dietary recommendations and treatment planning.
Healthcare operations under uncertainty. Robust and predictive-to-robust frameworks for operating-room scheduling, bed management, and downstream capacity, developed in collaboration with clinical partners.
Public-health surveillance and analytics. Real-time, county-level disease surveillance systems — most notably for measles and COVID-19 — that translate messy, distributed data into decision-ready information for public-health response.