Projects
Applied and professional projects in scientific machine learning and physics-based modeling.
Corn Nitrogen Response Modeling
Dose-response modeling of corn nitrogen fertilization, pairing canonical agronomic forms with modern machine learning and calibrated uncertainty
`meandre` - Differentiable Hydrology
Process-based hydrological modeling with automatic differentiation for gradient-based calibration and hybrid physics-AI models
tangent/suite
An open-source suite for reproducible, install-free scientific computing in the browser: seven JavaScript packages spanning data science, notebooks, and Bayesian inference.
`capyllary` - Differentiable Unsaturated Hydromechanics
A pure, backend-neutral Python library of physics laws for coupled unsaturated flow, poromechanics, and contaminant transport, differentiable end to end for adjoint-based calibration
`nuee` - Multivariate Analysis in Ecology
Analyse multivariée en écologie
Automated Plant Ionomics Analysis
Comprehensive automated workflow for science-based ionomics analysis in agricultural research