海角论坛

Personal statement

Dr Esmaeil Khedmati Morasae is a Lecturer B (Assistant Professor) in Management Science at the University of 海角论坛 Business School. His research focuses on the development and application of advanced systems and analytical methodologies to address complex challenges in health, healthcare, sustainability, and public policy.

His work centres on System Dynamics (SD), Participatory modelling, and hybrid simulation approaches (including SD鈥揇iscrete Event Simulation (DES)鈥揂gent Based Modelling (ABM) integration), with a strong emphasis on methodological innovation and rigorous analytical foundations. Alongside simulation modelling, he has substantial expertise in quantitative analytics and statistical modelling, including causal inference, longitudinal analysis, and data-driven policy evaluation. His research integrates systems thinking with robust statistical and computational techniques to enhance explanatory depth and decision relevance.

Dr Khedmati Morasae has applied these approaches across interdisciplinary domains, including health systems modelling, mental health service pathways, tuberculosis鈥揷limate change interactions, circular economy transitions (notably rare-earth material circularity in UK wind energy systems), and Net Zero housing policy. His work frequently bridges methodological development with applied policy challenges, ensuring both theoretical contribution and practical impact.

He currently holds a UKRI Policy Fellowship with the Scottish Government, focusing on embedding systems thinking within housing policy analysis and decision-making processes. More broadly, his research contributes to the advancement of hybrid operational research by integrating artificial intelligence with participatory modelling and problem-structuring methods, particularly in Group Model Building settings.

His programme of research aims to strengthen the role of systems modelling and analytics as rigorous, policy-relevant tools for understanding and intervening in complex socio-technical systems.