معرفی
Reza Skandari is an Assistant Professor of Health Operations at Imperial College Business School, affiliated with the Centre for Health Economics & Policy Innovation. He holds a PhD in Management Science from the Sauder School of Business, University of British Columbia, and previously worked as a Senior Research Analyst at the University of Chicago School of Medicine. His research focuses on applying interpretable AI, reinforcement learning, and stochastic optimization to healthcare operations and policy challenges, particularly in clinical decision-making, cost-effectiveness analysis, and health system efficiency.
His work spans methodologies such as large language models (LLMs), reinforcement learning, and decision analytical modeling, with applications in chronic disease management, oncology surveillance, diabetes treatment optimization, and healthcare resource allocation. Recent studies have addressed ctDNA surveillance for head and neck cancers, cost-benefit analyses of medical scribes, and long-term efficacy of diabetes medications.
Skandari has collaborated with institutions like the Centre for Translational and Policy Research of Chronic Diseases, producing interdisciplinary research at the intersection of operations management, health economics, and machine learning. His articles frequently explore trade-offs between clinical outcomes and economic costs, with a focus on actionable policy insights for healthcare systems.
- Education: PhD in Management Science (University of British Columbia), Sauder School of Business
- Labs/Affiliations: Centre for Health Economics & Policy Innovation, Imperial College Business School
- Grants/Advising: No specific grants mentioned in text; advises on policy-relevant operational research in healthcare
