Wesley Marrero

Professor Wesley Marrero received a Young Investigator Program Award from the Air Force Office of Scientific Research (AFOSR). The award provides $450,000 over three years to advance the scientific foundations of interpretable artificial intelligence for time-varying decision environments. Marrero will develop methods for learning optimal decision strategies with tree-like structures or under user-defined interpretability rules. The project is motivated by challenges that deployed medics face when making rapid triage and evacuation decisions in austere environments. "For AI tools to be effective and trusted by military leadership, they must adapt to fast-changing scenarios and deliver logical recommendations that can be easily understood," he said.

Professor Wesley Marrero was selected for an Operations Research & Data Science Faculty Fellowship at the Air Force Institute of Technology (AFIT). His appointment will focus on fundamental research in sequential decision-making with applications at the DoD. The overall goal is to develop decision-support techniques that account for noncompliance with AI-driven recommendations. "By recognizing that optimal solutions may not always be adopted in practice, this work will help establish a basis for operationally-acceptable automated decision-support throughout the Air Force and Department of Defense," said Marrero.

PhD student Zequn "Vincent" Chen and Professor Wesley Marrero co-authored "A survey on optimization and machine learning-based fair decision making in healthcare" published in Health Care Management Science. The review examines how fair AI and mathematical optimization can improve areas like patient scheduling, disease diagnosis, and treatment recommendations. It identifies potential sources of bias in existing literature, classifies different bias mitigation strategies, and evaluates fairness metrics that help verify whether outcomes are equivalent for privileged and unprivileged groups. "By analyzing the trade-offs of each method, this research facilitates more informed and transparent decision-making in health care," said Marrero.

PhD student Jiahui "Gary" Luo and Professor Wesley Marrero,  with researchers at U Michigan, developed a new simulation framework to analyze liver transplant decisions, which was published in IEEE's 2025 Winter Simulation Conference. The team created a continuous-time simulation that models patient health and organ arrivals while mimicking real-world, varied organ acceptance practices. "The study concludes that high selectivity is a major obstacle to saving lives. Because small quality differences have modest survival effects, accepting a broader range of medically suitable organs can significantly reduce waiting times and maximize the lifesaving potential of the donor pool," said Marrero.

Priyanshu Alluri '26, PhD student Zequn Chen, and Professor Wesley Marrero presented a socially-fair framework, published in Journal of the American Medical Informatics Association - Open, that ensures homogeneous clustering performance across demographic groups while minimizing within-cluster variability. "The study integrates fairness considerations into clustering algorithms to reduce discrepancies in risk stratification and provides insights into socioeconomic drivers of student well-being," said Marrero.

PhD student Jiahui Luo and Professor Wesley Marrero—with quantitative biomedical sciences PhD student Guofang Ma and Miranda Scully '26—co-authored "Modeling the impact of social determinants on breast cancer screening: a data-driven approach" published in Frontiers in Medicine. "The study identified opportunities for healthcare organizations to transform sociodemographic data into targeted, facility-level intervention strategies while adapting to payer incentives and addressing screening gaps," said Marrero.

Professor Wesley Marrero received the INFORMS MIF Best Paper Award as co-author of, "Interpretable Policies and the Price of Interpretability in Hypertension Treatment Planning" published in Manufacturing & Service Operations Management. The paper uses optimization to design clinically intuitive hypertension treatment protocols that greatly outperform clinical guidelines.

Professor Wesley Marrero will co-lead a project funded by the American Medical Association's ChangeMedEd Innovation Grant Program, which adopts the holistic "Precision Well-Being" approach to create personalized wellness solutions for optimal learning and wellness in medical school. The team includes Thayer PhD student Zequn Chen, Geisel professors Thomas Thesen and Matthew Duncan, and LeChauncy Woodard at the University of Houston College of Medicine.

Professors Liz Murnane, Vikrant Vaze, and Wesley Marrero are lead faculty on a team selected as one of 34 semifinalists for the inaugural NSF Regional Innovation Engines competition—spanning nearly all key technology areas and societal and economic challenges highlighted in the "CHIPS and Science Act." A partnership with UMass Lowell, their proposed engine is titled, "Advancing Health Equity Through Digital Technologies, Data Infrastructure, and Artificial Intelligence." Each Engine could receive up to $160 million over 10 years.