Research project

🐢 Interface for Running NetLogo Simulations from R

Infrastructure and tooling for the NextGen Research DataStream (NRDS)

A Python based kernel to perform spatial (environmental) impact assessment

Heterogenous Graph Attention Transformer for high-resolution, distributed spatiotemporal flood prediction. Published at ACM SIGSPATIAL 2025.

Hydrological Model Continuum (HMC) – Open-source distributed hydrological model for simulation of water cycle processes, including runoff, soil moisture, snow, and routing.

Spatiotemporal Gaussian process modeling for environmental data: non-stationary PDE prior, deep kernels, multi-fidelity fusion, and A-optimal sampling.非稳态 PDE + 核深度学习 + 多保真 Co-Kriging + 主动采样的物理约束克里金方法，用于复杂时空环境建模与预测

Complementary repository with data and code for Wolf & Tollefsen, 2021.

Numerical interpolation and approximation of water pollution data to construct continuous spatial pollution maps.

Advanced framework combining 2D contaminant transport simulation (advection–diffusion) with machine learning to classify ecological risk (Low/Medium/High) and generate dashboards, GIFs, and reports.

C++ systems development for environmental modeling, 3D visualization, and performance-critical applications. Combining computational efficiency with domain expertise in environmental science and data systems.

Data-driven river water quality modeling using MATLAB and HSY algorithm with simulation and optimization techniques

Operational HAB forecasting for the San Jose Lagoon (in San Juan, PR) using weekly chlorophyll-a regression and bloom-risk classification.

Code and processed data accompanying the MSc thesis Integrating Dynamical Systems and Machine Learning for Modeling and Predicting Decay Across Wood Treatments, conducted at DTU in collaboration with the Danish Technological Institute.

Enhanced Rock Weathering Analysis using USGS Alaska Geochemical Database

Multivariate GLM/GAM pipeline modeling fish community structure responses to SST, wind, chlorophyll, and kelp biomass forcing in the California Current ecosystem

A pioneering methodological framework for environmental modeling in the LIFE A_GreeNET project using ENVI-met. This protocol integrates Rhinoceros, Grasshopper, and the Morpho plugin to create a standardized approach for urban environmental simulations.

❄️ 🌊 SHYBOX is a modular hydrological processing framework designed to run reproducible workflows using versioned environmental datasets provided by the shydata repository.

This model is use to assess the suitability of current and future locations for commercial wind farm construction across the Conterminous United States (CONUS). Aggregated datasets have been prepared for all states and the CONUS. Model script: "LR_Equation_Code.py", "CA_Model_Code.py". Model instructions: "Model Description and Instructions.pdf".

R toolbox for LT SWAT: processing point source data, load calculations, and risk assessments.