This article explores the theory behind explainable car pricing using value decomposition, showing how machine learning models can break a predicted price into intuitive components such as brand premium, age depreciation, mileage influence, condition effects, and transmission or fuel-type adjustments.

An interpretable system that models the future of work as an equilibrium under AI-driven forces. Instead of predicting job loss, it decomposes workforce disruption into automation pressure, adaptability, skill transferability, demand, and AI augmentation to explain stability, tension, and transition paths by 2030.

A model which simulates coastal flooding, and evaluated the economic benefits of climate adaptation strategies.

Open repository for collaborative research on economic models, integrating theory, simulations, and data. Contribute papers, code, and datasets to advance understanding of economic modeling and policy analysis.

NDA-safe excerpts of math & economics modeling tasks for LLM reasoning evaluation and numerical verification.

Detect U.S. housing market bubbles using macroeconomic signals. Forecast HPI, score speculative risk, and visualize insights using a fully modular, cloud-native GCP pipeline.

🤖 Analyze the future of work with the Workforce Disruption Equilibrium Engine, a system for understanding job changes in an AI-driven world.