Zein Khraizat
Doctoral Researcher @Ucl Institute For Sustainable Resources
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WORK HISTORY
Doctoral Researcher @Ucl Institute For Sustainable Resources
London, GB
EDUCATION
Beirut International School
High school
UCL
Doctor of Philosophy - PhD, PhD in Macroeconomic Modelling and Structural Transformation
American University of Beirut
Bachelor's degree, Agricultural Engineering
American University of Beirut
Master of Science (MS), Irrigation and Water Resources
ABOUT ZEIN KHRAIZAT
I design and lead macroeconomic and financial modelling systems for forward-looking risk assessment, focusing on how structural shifts driven by technology, policy, and market dynamics translate into portfolio risk, capital allocation decisions, and economic outcomes under uncertainty.My work centres on building integrated modelling frameworks that embed resource constraints, regulatory regimes, and institutional structures directly into economy-wide systems. These frameworks support scenario analysis and stress testing by linking macroeconomic, policy, and sectoral drivers to portfolio-level and asset-level outcomes across heterogeneous regions and sectors.I develop dynamic modelling architectures that capture non-linear adjustments in productivity, capital allocation, sectoral reallocation, and fiscal capacity. This includes constructing scenario engines and policy-driven frameworks that allow for consistent evaluation of risk exposures, transition pathways, and trade-offs under alternative economic and regulatory conditions.Across research and advisory settings, I have built structured modelling systems used by senior executives and investors to assess risk, evaluate strategic positioning, and inform capital allocation. This involves integrating complex datasets into coherent analytical frameworks, formalising constraints and objectives within optimisation systems, and translating model outputs into clear, decision-grade insights.My focus is on understanding how structural transformation reshapes risk, returns, and allocation dynamics, and on designing modelling systems that support robust decision-making in environments characterised by uncertainty, regulatory change, and long-horizon investment considerations.
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