AI-Enhanced Ecosystem Modeling

To address limitations of traditional models in capturing system heterogeneity and nonlinear responses, my recent work integrates artificial intelligence (AI) with process-based modeling through knowledge-guided machine learning (KGML) frameworks. These hybrid approaches encode mechanistic constraints within data-driven architectures, enabling improved predictions of biogeochemical responses, plant growth, and water use across heterogeneous landscapes.