The same methods that live in the research portfolio, running where decisions carry real cost: industrial materials, commodity markets, aerospace and banking.
First team member of a materials-industry corporate venture function. Built a demand-forecasting platform now protected by a granted patent (LU103146), plus a CO2/sustainability platform and the group’s first digital-twin and replenishment initiatives.
Built a RAG and causal-intelligence engine that turns market news into queryable, causal signals. Optimization models now identify each customer’s optimal purchase timing and hedge ratio, scaled across thousands of features per commodity.
Built forecasting and mathematical optimization models to strengthen production planning and supply-chain decision-making.
Supported stress-testing of global loan and mortgage portfolios within liquidity and crisis-planning frameworks aligned to EBA and Basel requirements.
Also completed: loan-eligibility data mining for consumer lending, and machine-learning-driven sponsorship and fan-experience analytics for professional sports.
A machine-learning method for demand forecasting in a local-global model, improving production planning, inventory and logistics — assigned to thyssenkrupp.