Mechanism Design for Climate Finance: Machine Learning & Game-Theoretic Approach

Using machine learning, multi-agent simulation, and game theory, this team is designing mechanisms to improve ESG rating integrity and incentivize low-carbon economic behavior. Their models aim to reduce greenwashing and simulate transition risks. Digital twins and scalable reinforcement learning approaches are used to test financial system responses under new policy regimes.