Abdullah Al Faisal

• Designed AI-enabled spatial models for forecasting and gap-filling in global energy and material flow datasets, improving data completeness by over 30 percent.
• Built an open-source Python package to generate and manage spatiotemporal datasets across 250+ human and Earth system variables at grid-level resolution for 220+ countries, integrating satellite imagery, census, and socioeconomic data to enable large-scale environmental, climate, and human-Earth system analysis.
• Developed gravity-based and network models linking resource extraction to end-use sectors for energy and material systems.
• Applied ML gap filling and predicted modeling using with cross-validation and error metrics.
• Mentored and trained 120+ students and collaborators in quantitative analysis, environmental systems, and climate hazards while delivering reproducible analytical pipelines used by international applied research teams.

• Led mission-level GIS systems as the technical focal point, supporting humanitarian medical response across water and sanitation, logistics, security, outreach, and coordination functions in Rohingya refugee camps.
• Coordinated, trained, and supervised GIS, WatSan & outreach field teams, including leading of a 20+ member refugee data collection team, enabling camp-level infrastructure and health data capture.
• Designed and deployed geospatial data collection systems through operational dashboards using Kobo Toolbox, ArcGIS Survey123, Collector, Enterprise, and AGOL.
• Managed and analyzed geospatial data for water networks, operation & maintenance, fecal sludge management, and hygiene promotion, producing decision-ready maps and analyses.
• Coordinated geospatial activities with local authorities and international partners including UNICEF, IOM, UNHCR, and NGOs.

• Managed GIS and remote sensing activities across 10+ national and international climate change (CC) and water management projects, including but not limited to: CC forecasting & participatory scenario development, sea level rise in coastal region, CC risk assessment in roads and low-lying flood potential region, preparation of storm water management plan for Thimphu, Bhutan, among others.
• Developed watershed and urban drainage models using ArcSWAT, ArcHydro, and SWMM, including DEM-based drainage connectivity, catchment delineation, slope, elevation, and discharge analysis.
• Conducted flood risk, inundation, storm water management, and road vulnerability analyses, including coastal crop damage assessment.
• Performed land use and land cover classification, impervious surface estimation, and DEM analysis from satellite imagery.
• Applied multi-criteria analysis to identify critical drainage zones and priority infrastructure interventions.
• Led field surveys, data verification, cadastral map digitization, and spatial data integration, coordinating with national and international government agencies.
• Prepared technical reports, maps, and presentations, revising deliverables based on client and stakeholder feedback.

• Programming: Python, R, Google Earth Engine (JavaScript), ENVI IDL

• AI / ML & Modeling: machine learning, deep learning, predictive modeling, regression and tree-based models, neural networks, network and gravity models, material and energy flow models, statistical modeling

• Geospatial AI & Analysis: GeoAI, geospatial big data, spatial feature engineering, DEM analysis, land use and land cover classification, LiDAR, photogrammetry, UAV, Web GIS

• GIS Platforms: ArcGIS Pro, ArcGIS Enterprise, ArcGIS Online (AGOL), QGIS, ERDAS Imagine, ENVI, SNAP

• Libraries & Tools: GeoPandas, pandas, NumPy, xarray, rasterio, GDAL, arcpy, scikit-learn, TensorFlow, PyTorch, PyCaret, networkx

• Field & Surveys: Survey123, Kobo Toolbox, ArcGIS Collector