about me
I am a geospatial data scientist.
My work is cross-disciplinary, spanning remote sensing, computer vision, and geospatial analysis. Specific areas of interest include machine learning, deep learning, XAI (eXplainable Artificial Intelligence), generative AI, hyperspectral imaging, UAVs (drones), 3D modeling, computational imaging, and photogrammetry.
In my current role as Data Scientist at the World Bank Independent Evaluation Group, I lead the development and application of image-based methodologies (including remote sensing images and street-view photos) for the evaluation of international development projects.
I completed my postgraduate education at the University of Oxford and the University of Edinburgh.
selected papers
Extracting Meaning from Textual Data for Evaluation (Book chapter in “Artificial Intelligence and Evaluation”)
With Harsh Anuj, Ariya Hagh, Estelle Raimondo, and Jos Vaessen
The relevance of development policies to confront crisis situations: World Bank’s early response to Covid-19
With Dominik Naeher and Raghavan Narayanan
Leveraging Imagery Data in Evaluations. Applications of Remote-Sensing and Streetscape Imagery Analysis
Poverty Mapping. Innovative Approaches to Creating Poverty Maps with New Data Sources
With Jessica Meckler, Gonzalo Hernández Licona, and Jos Vaessen
Impacts of energy efficiency projects in developing countries: Evidence from a spatial difference-in-differences analysis in Malawi
With Dominik Naeher and Raghavan Narayanan
Cash for Coolers or Sustainable Lighting? Assessing Different Components of a Large-Scale Energy Efficiency Program in Mexico
With Dominik Naeher and Raghavan Narayanan
Relevance of the World Bank Group’s Early Response to COVID-19: A Cross-Country Sector Analysis
With Dominik Naeher and Raghavan Narayanan
