Neeraj has led a wide range of projects with a particular focus on applying economic frameworks to EO data. His experience includes working with development finance institutions (World Bank and EBRD), public (LSE, Oxford University, Birmingham University, Bristol University, Yale University, The Energy and Resources Institute and Indian Space Research Organisation) and private entities in the extraction of derivative products and indices from EO data, with a major focus on cities and infrastructure, development economics and natural resources management. As a GIS specialist, he led the EO team on the World Bank funded ‘Urbanisation in Developing Countries’ and ‘Spatial Development of African Cities’ projects based at the London School of Economics and Oxford University, where he managed the development of automated algorithms to extract economic indices from high resolution satellite imagery in over 60 Sub-Saharan African cities.
Besides EO, he has a strong background and expertise in computer vision, machine learning, GIS, big data science and spatial economics. Neeraj’s doctoral studies from the University of Cambridge utilises deep machine-learning algorithms to extract and classify urban retail infrastructure from earth observation and volunteered geographic information data. He holds an MSc in Geoinformatics from The Energy and Resources Institute (India) and a BSc (Hons) in Physics from University of Delhi.