About
I am 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.
My research develops AI-driven decision-support systems for complex operational problems, with applications in healthcare management and public policy. I combine methods from operations research, machine learning, and optimization to build tools that improve managerial decision-making under uncertainty. My work has appeared in leading medical journals — including JAMA and The Lancet Infectious Diseases — and is under review at top operations venues such as Operations Research, the European Journal of Operational Research, and the INFORMS Journal on Optimization.
I earned my Ph.D. in Civil and Systems Engineering from Johns Hopkins University, working on healthcare operations optimization and inverse-optimization methods, and I was a Ph.D. researcher at MIT's Computer Science & Artificial Intelligence Laboratory (CSAIL).
Most recently, I developed the U.S. Measles Tracker at Johns Hopkins — a county-level surveillance system providing timely case data and visualizations. This work was published in JAMA and has been featured across national media as a public-health resource during the ongoing measles outbreak.
News
Recent talks, publications, grants, and media — most recent first.
Jul 2026
Five talks featuring our work scheduled at the INFORMS Healthcare Conference 2026 in Raleigh, NC (Jul 28–30) — spanning personalized dietary recommendations, robust surgery and bed scheduling, and statistical inference for inverse optimization.
Jul 2026
Named Co-Investigator (AI Data Science Core) on the Letter of Intent for the Center for Translation in Metabolic Therapeutics, Artificial Intelligence and Nutrition Science (TITANS), submitted for the LSRI Transformational Science Team Award.
Jul 2026
Our talk “Non-identifiability and Statistical Inference in Inverse Optimization” and poster “From Prediction to Protection in Surgery Scheduling” presented at the MSOM 2026 Conference, Harvard Business School.
May 2026
Submitted the manuscript “A Predictive-to-Robust Framework for Rolling-Horizon Operating Room Scheduling with Downstream Capacity Management” to Computers & Industrial Engineering.
May 2026
Measles surveillance work featured as a Jeopardy! clue.
Apr 2026
Approved to chair the session “AI and Analytics for Public Health Surveillance and Emergency Response” in the PSOR cluster at the INFORMS Annual Meeting 2026, San Francisco.
Mar 2026
Submitted “From Non-Identifiability to Goal-Integrated Decision-Making in Parametric Inverse Optimization” to Operations Research, and two papers to the IEEE J-BHI special issue on AI-based solutions for dietary assessment.
Feb 2026
The U.S. Measles Tracker cited by The Atlantic in “The Deaths Doctors Never Thought They'd See in the U.S.”
Jan 2026
Chaired and moderated three sessions on AI-Driven Healthcare, and served as a panelist on the “Socio-Technical Ecosystems for Future Digital Health” symposium, at HICSS 59 (Maui, HI). Also attended the HICSS 59 Junior Faculty Consortium.
Nov 2025
Published “Near-Real-Time Measles Surveillance: How Analytics Can Help Transform Public Health Response” in OR/MS Today.
Oct 2025
Towson University News: “TU professor publishes study on measles tracking in the Journal of the American Medical Association.”
Sep 2025
Research letter on measles tracking featured in the JAMA Editor's Summary and covered by CIDRAP and This Week in Virology.
Sep 2025
Paper published: “Tracking County-Level Measles Cases in the US,” JAMA (2025), with Ensheng Dong and Lauren Gardner.
Research
I develop AI-driven decision-support systems for complex operational problems, combining operations research, machine learning, and optimization to improve decision-making under uncertainty — with applications across healthcare management and public policy.
Funded Research
Development of an AI-Powered Decision-Support System for Healthy Eating
AI2AI — JHU + Amazon Initiative for Interactive AI · Johns Hopkins University · 2026 · $375,000 (Direct Costs)
Role: Co-Investigator (PI: K. Ghobadi; Co-PI: L. Appel)
Developing inverse-optimization and machine-learning methods for personalized dietary recommendations.
Working Papers
Closed-Loop OR Scheduling Under Operational Uncertainty
In Preparation
Non-Asymptotic Bounds for Parameter Estimation in Inverse Optimization Using Concentration Inequalities
In Preparation
Maximum Likelihood Estimation and Confidence Regions for Inverse Convex Optimization
In Preparation
Automated Radiation Therapy Treatment Improvement Through Optimization Models
In Preparation
Supervised Inverse Optimization
In Preparation
Smart Surgical Scheduling Tool: An Optimization Model with Integrated Perioperative Information Input
In Preparation
Publications
Full list available on Google Scholar and in my CV.
Published & In Press
Tracking County-Level Measles Cases in the US
JAMA (2025)
Evolving Patterns of COVID-19 Mortality in US Counties: A Longitudinal Study of Healthcare, Socioeconomic, and Vaccination Associations
PLOS Global Public Health (2024)
The Johns Hopkins University CSSE COVID-19 Dashboard: data collection process, challenges faced, and lessons learned
The Lancet Infectious Diseases (2022)
Under Review & Preprints
Under Review
Solution Prediction Dominates Parameter Prediction Under Generic Non-Identifiability: Connecting Inverse Optimization and Predict-then-Optimize
European Journal of Operational Research
Under Review
A Predictive-to-Robust Framework for Rolling-Horizon Operating Room Scheduling with Downstream Capacity Management
Computers & Industrial Engineering
Under Review
Similarity-Guided Inverse Optimization for Personalized Dietary Recommendations
IEEE Journal of Biomedical and Health Informatics
Under Review
Recovering Food Choice Preferences via Inverse Reinforcement Learning
IEEE Journal of Biomedical and Health Informatics
Under Review
From Non-Identifiability to Goal-Integrated Decision-Making in Parametric Inverse Optimization
Operations Research
Under Review
You Are What You Eat: A Preference-Aware Inverse Optimization Approach
INFORMS Journal on Optimization
Under Review
Improving Observed Decisions for Partially Known Optimization Problems Through Inverse Optimization, with Application to Radiation Therapy Treatment Planning
European Journal of Operational Research
Preprint
Optimal Resource and Demand Redistribution for Healthcare Systems Under Stress from COVID-19
Preprint (2020)
Preprint
An Open-Source Dataset on Dietary Behaviors and DASH Eating Plan Optimization Constraints
Preprint (2020)
Magazine Articles & Non-Peer-Reviewed
Near-Real-Time Measles Surveillance: How Analytics Can Help Transform Public Health Response
OR/MS Today (2025)
Detecting and Mitigating Disparities in Preventive Care and Healthcare Delivery: The Role of Artificial Intelligence and Operations Research
OR/MS Today (2023)
Monkeypox: Another Public Health Crisis
OR/MS Today (2022) · Featured on the cover
Navigating the Use of ChatGPT in Education and Research: Impacts and Guidelines
OR/MS Tomorrow (Summer 2023)
OR/MS Tomorrow Industry Series: OR/MS in Finance
OR/MS Tomorrow (Summer 2023)
A Comprehensive Guide on INFORMS Student Chapters
OR/MS Tomorrow (Winter 2022)
Extended Abstracts
Learning DVH Criteria in Radiation Therapy Treatment Planning
Medical Physics (2022)
Talks & Presentations
Selected invited talks and conference presentations. A complete list appears in my CV.
Upcoming & Recent
Jan 2027
Real-Time Public Health Surveillance as a Socio-Technical Ecosystem
HICSS-60 Symposium on Strategic Foresight for Socio-Technical Ecosystems · Hawaii Island, HI
Nov 2026
Similarity-Guided Inverse Optimization for Personalized Dietary Recommendations
INFORMS Annual Meeting · San Francisco, CA
Jul 2026
Five presentations across dietary recommendation, robust surgery & bed scheduling, and inference for inverse optimization
INFORMS Healthcare Conference · Raleigh, NC
Jul 2026
Non-identifiability and Statistical Inference in Inverse Optimization; From Prediction to Protection in Surgery Scheduling (poster)
MSOM Conference · Harvard Business School, Boston, MA
May 2026
Real-Time County-Level Measles Surveillance and AI-Augmented Monitoring During the 2025 U.S. Outbreak
Conference on Health IT and Analytics (CHITA) · Washington, D.C.
Jan 2026
Real-Time Public Health Surveillance as a Socio-Technical Ecosystem
HICSS-59 Symposium on Socio-Technical Ecosystems for Future Digital Health · Maui, HI
Jan 2025
Inverse Optimization for Personalized Nutritional Guidance: Aligning Preferences with Nutritional Needs
Department of Health Sciences, Towson University
Oct 2022
A Data-Driven Framework to Recommend Improved Radiation Therapy Treatment Plans
INFORMS Annual Meeting · Indianapolis, IN
Conference Organization
Jan 2027
Mini-track Chair — AI-Driven Healthcare: Bridging Systems Science and Clinical Practice
HICSS 60 · Hawaii Island, HI
Oct 2026
Session Chair — AI and Analytics for Public Health Surveillance and Emergency Response
INFORMS Annual Meeting · San Francisco, CA
Jul 2026
Session Chair — Integrated AI and LLMs in Healthcare Modeling; and Data-Driven Inverse Optimization
INFORMS Healthcare Conference · Raleigh, NC (with Kimia Ghobadi)
Jan 2026
Mini-track Chair — AI-Driven Healthcare: Bridging Systems Science and Clinical Practice
HICSS 59 · Maui, HI
May 2023
Session Organizer
POMS 32nd Annual Conference · Orlando, FL (with Kimia Ghobadi and Fardin Ganjkhanloo)
Experience & Education
Appointments
Towson University — College of Health Professions
Assistant Professor of Healthcare Management
August 2025 – Present
Research focus: Operations analytics; AI/ML for healthcare decision systems
Teaching: Healthcare systems; health information management
Courtesy appointments: Johns Hopkins Center for Systems Science & Engineering; Johns Hopkins Data Science and AI Institute (DSAI)
Johns Hopkins University
Postdoctoral Fellow, Center for Systems Science & Engineering
March 2025 – September 2025
Research in healthcare systems engineering and epidemiological surveillance.
Massachusetts Institute of Technology
Ph.D. Researcher, Computer Science & AI Laboratory (CSAIL)
June 2024 – December 2024
AI applications for healthcare operations and decision-making systems.
Education
Johns Hopkins University, Baltimore, MD
Ph.D. in Civil and Systems Engineering · M.S. in Systems Engineering
2019 – 2025
Dissertation committee: Todd McNutt (chair), Kimia Ghobadi (advisor), Tinglong Dai, Yury Dvorkin, Takeru Igusa, Susu Xu, and Ritu Agarwal.
Sharif University of Technology, Tehran, Iran
M.Eng. in Transportation Engineering
2016 – 2018
Specialization in transportation systems optimization.
Sharif University of Technology, Tehran, Iran
B.Sc. in Civil Engineering
2012 – 2016
Graduated in the top 20% of the class; honored as a “Brilliant Talented Student” by Iran's National Elites Foundation.
Honors & Awards
- Selected for the HICSS 59 Junior Faculty Consortium (2026)
- Teaching Assistant Award for excellence in teaching and dedication to engineering education, Johns Hopkins University (2022)
- Top 20% in Civil Engineering, class of 2012, Sharif University of Technology
- Straight invitee to the M.Sc. program in Highway & Pavement Engineering, Sharif University of Technology (2016)
- “Brilliant Talented Student,” Iran's National Elites Foundation (2014)
- Ranked 221st (top 0.085%) of 260,000+ in the National University Entrance Exam, Mathematics & Physics (2012)
Teaching & Service
Teaching
Towson University
HLTH 207: Health System of the U.S.
Summer 2025, Fall 2025 (2 sections), Spring 2026 (2 sections)
Course evaluations (Summer & Fall 2025):
- Enrollment: 55 students
- Overall teaching effectiveness: 4.3 / 5.0
- Overall demonstrated knowledge: 4.4 / 5.0
- Response rate: 83%
HCMN 435: Health Information Management
Spring 2026
Johns Hopkins University
Instructor — EN.500.111 HEART: Healthcare System Engineering (Fall 2023)
- Overall instructor evaluation: 5.00 / 5.00
- Overall course quality: 4.75 / 5.00
Teaching Assistant — Data Science: Artificial Intelligence (Carey Business School, 3 semesters); Introduction to Mathematical Decision Making; Operations Research.
Guest Lectures — Operations Research (Gurobi-based optimization, Fall 2023–2025); Civilization Engineered.
Service & Leadership
Professional Service
- Peer Reviewer, PLOS Global Public Health (2024–2026)
- President, Johns Hopkins University INFORMS Student Chapter (2022–2024)
- Editorial Board Member, OR/MS Tomorrow (2022–2024)
Professional Affiliations
- INFORMS
- Manufacturing & Service Operations Management Society (MSOM)
- Health Applications Society (HAS)
- American Association of Physicists in Medicine (AAPM)
- Society for Industrial and Applied Mathematics (SIAM)
Notable Projects
U.S. Measles Tracker — Johns Hopkins CSSE
2025
Developed and maintain a county-level measles tracking system providing timely epidemiological data and visualizations — a public-health resource during the ongoing outbreak, published in JAMA and covered by CIDRAP, HuffPost, and public-health podcasts.
COVID-19 Dashboard — Johns Hopkins CSSE
2020
Contributed to data maintenance and monitoring for the globally recognized JHU COVID-19 Dashboard, coordinating with state health organizations to ensure timely, accurate county- and state-level reporting during the early pandemic.
Selected Media Coverage
- Measles work featured as a Jeopardy! clue (May 2026)
- The Deaths Doctors Never Thought They'd See in the U.S. — The Atlantic (Feb 2026)
- TU professor publishes study on measles tracking in JAMA — Towson University News (Oct 2025)
- TWiV 1254: Clinical Update with Dr. Daniel Griffin — This Week in Virology (Sep 2025)
- JAMA Editor's Summary featuring measles case tracking — JAMA Network (Sep 2025)
- Researchers introduce tool featuring timely county-level US measles data — CIDRAP (Sep 2025)
- RFK Jr. Boasts About Major Measles Outbreak Response — HuffPost (Sep 2025)
- U.S. Measles Cases Hit Highest Level Since Declared Eliminated in 2000 — JHU Bloomberg School of Public Health (Jul 2025)
- One size doesn't fit all: An AI approach to creating healthy personalized diets — Malone Center (Nov 2022)
Contact
Office
Department of Health SciencesTowson University
8000 York Road
Towson, MD 21252