Research

I am broadly interested in using geospatial data and machine learning for a wide range of applications. Some of the key topics I have worked on or continue to explore include:

Flood Mapping & Impact Assessment

• Global Flood Mapper

Urban Spatial Analysis

• Building Height Mapping: Estimating city-scale building heights from satellite images
• Urban Growth Models: Simulating land-use change and urban expansion
• Street Network Analysis: Extracting road hierarchy and connectivity using COINS

Population & Socio-Economic Data Modeling

• Downscaling gridded population data for improved flood exposure estimates

Predicting Deforestation & Land Cover Change

• Applying deep learning models to predict deforestation in the Amazon

Open-Source Tools

I am passionate about open-source geospatial software development and have created tools to support research and real-world applications. Some of my notable projects include:

• PyRSGIS – A Python package for raster data processing, soon to include ML workflows for geospatial analysis
• Global Flood Mapper – A Google Earth Engine tool for rapid flood mapping
• COINS – A Python-based tool for street network continuity analysis

I am always looking to improve and expand these tools. If you’re interested in collaboration or have ideas, feel free to reach out!