Embedded Files
Investment Decision Support
Investment Decision Support
Resource allocation requires more than simple forecasting. We build structural economic models to quantify the long-term ROI of Research & Development (R&D) and technology investments. By analyzing technology adoption curves and benefit attribution, we provide the data-driven confidence needed to justify high-stakes portfolio decisions.
Risk Management
Risk Management
Standard risk models often fail to account for the biological complexity of agricultural and supply chain systems. We specialize in Probabilistic Bio-Economic Assessments, analyzing spatial-temporal data to predict the economic impact of biotic risks (pests, pathogens) and abiotic shocks (climate, weather). We help clients design mitigation strategies for sustainable risk management.
Production Optimization
Production Optimization
Moving beyond averages to precise, heterogeneous insights. We utilize Bayesian models and production function analysis to identify the causal drivers of yield and performance. Whether optimizing nitrogen fertilizer usage or streamlining manufacturing inputs, we isolate the true signals of productivity to reduce waste and maximize output.
Featured Projects
Featured Projects
R&D Investment & Technology Adoption
R&D Investment & Technology Adoption
Challenge: Linking technology investment decisions to actual field-level losses and adoption rates (e.g., Soybean Aphid control).
Solution: Led an interdisciplinary analysis connecting biological pest pressure data with economic investment models.
Outcome: Created a decision-support framework for identifying the most high-value R&D targets, ensuring research dollars are directed toward technologies with the highest probable adoption and impact.
Bio-Economic Risk Assessment
Bio-Economic Risk Assessment
Challenge: Quantifying the economic threat of multi-peril pathogens (e.g., Wheat Rust) on global food security.
Solution: Developed a probabilistic loss and investment assessment model using large-scale spatial panel data.
Outcome: Identified causal drivers for crop insurance and provided investment assessments for international stakeholders to mitigate long-term biotic risks.
Optimizing Nitrogen Inputs for Production Efficiency
Optimizing Nitrogen Inputs for Production Efficiency
Challenge: Addressing the trade-off between yield maximization and environmental impact in corn production.
Solution: Implemented a hierarchical random coefficient model to identify the spatiotemporal heterogeneous causal effects of nitrogen fertilizer on yield.
Outcome: Delivered "nudging" strategies that optimized input use, maintaining productivity while reducing water pollution risks.
Page updated
Google Sites
Report abuse