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.

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

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.

Particle-based Python demo of synthetic plume transport through a variable wind field using advection, random-walk diffusion, eddy/shear flow, and density visualization.

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

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.

Enhanced Rock Weathering Analysis using USGS Alaska Geochemical Database

Synthetic radiological plume modeling and sensor-network analysis pipeline with Gaussian plume transport, detector thresholds, source reconstruction, Monte Carlo uncertainty, and MATLAB/Python figures.

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