I am a systems scientist aiming to produce policy-relevant research by integrating management, systems and health sciences with a strong emphasis on data-driven analysis and modeling. I have BSc and MSc degrees in Industrial Engineering from Bogazici University, an MSc in Physiology from McGill University, and completed my PhD at MIT Sloan School of Management, System Dynamics Research Group. With a background in industrial engineering, management and health sciences, I am drawn to systemic problems of chronic nature, which encompass typical constraints and approaches with important managerial implications for the societal domain, coming from medical or non-medical contexts. My training is multi-disciplinary, and I have both collaborated and published with experts in management, systems sciences, health sciences, and engineering to solve complex managerial problems with important policy implications for the societal domain. My current projects at HSPH include dynamic modeling of chronic and cardiovascular diseases for Malaysia; obesity and diabetes in the Middle East; global risk factors for hypercholesterolemia; and health systems research using complex systems methodologies, such as system dynamics, agent-based, and network sciences. My research experience and interests can be summarized in three major, complementary areas:
i) Dynamic modeling for policy analysis (public health, medicine, environment, sustainability, or any other complex system problem)
ii) Specific application areas in health policy and management as an overarching theme at various levels (micro, mezzo, macro), relevant to clinical/public health research and management (such as evidence-based guideline formation, cancer screening, chronic and cardiovascular disease management, disease biomarkers, physiologically oriented disease modeling, NCDs, cardiovascular diseases and obesity)
iii) The underlying theoretical and empirical methods to cultivate research in the first two domains
One of my main lines of research is the investigation of the universal problem of evidence-based development of sound and reliable clinical practice guidelines. The theory and resulting models I build are grounded in empirical evidence-base and use a mix of quantitative and qualitative methods and data, a dynamic modeling approach to complex systems, statistical data analysis, and other decision-analysis tools to explain long-term trends in population screening and related problems within the context of developed countries. I have collected evidence for significant variations in screening trends in developed countries, and have been working on building novel models and policy decision support tools to inform and complement evidence-based clinical practice guidelines (CPGs).
Please contact me for possible collaborations and available positions in my research group.
Email: firstname.lastname@example.org and email@example.com