Research project

🐢 Interface for Running NetLogo Simulations from R

Infrastructure and tooling for the NextGen Research DataStream (NRDS) - Datastream Orchestration on AWS

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

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

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

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

Enhanced Rock Weathering Analysis using USGS Alaska Geochemical Database

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.

Deterministic simulation framework for bio-stabilizing lunar regolith using spray dynamics, curing physics, and validated system models.

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".

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

Interactive reservoir water balance and ensemble forecasting application. Integrates Sentinel-2 data, GLEAM evaporation, and robust seasonal trend analysis via a modular Streamlit dashboard

High-performance computing project for simulating subsea oil–water jet breakup and droplet dispersion using a multicomponent Lattice Boltzmann Method (LBM) on NVIDIA GPUs with CUDA C++.

Network-based modeling of aquatic food system resilience under environmental and human-induced stress. This project uses data science and network analysis to study sustainability, vulnerability, and resilience indicators in fisheries and aquatic ecosystems, with a focus on Red Sea relevant systems.