Claire
Gorman
Hanly



Claire Gorman Hanly is an American computer scientist and environmental designer. Her research and practice focus on the implementation of deep learning-based computer vision methods in built and natural environments, with applications in regenerative agriculture, remote sensing of hydrology, and cultural landscape preservation. 

Claire’s work ranges geographically across glaciers and caves, river deltas and grain supply-sheds, Arctic wilderness and subtropical cities. It ranges methodologically across scientific research, creative curation, and speculative tool-building. She has collaborated with technology companies, research labs, and the US National Park Service as well as her most recent role in co-curating the 19th International Architecture Exhibition at La Biennale di Venezia.

Claire is currently pursuing two Master’s degrees at MIT: an MCP in Environmental Policy and Planning, and an MS in Computer Science. Her Bachelor’s degree is in Computer Science and Architecture, from Yale University.


clairego@mit.edu
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CIBO Technologies


Generalist data science contributions to the Computer Vision team at venture-backed regenerative agriculture startup CIBO Technologies. Projects included scaling nationwide road data acquisition and rasterization for integration in a cropland prediction workflow, training a multi-billion-parameter crop detection model using augmented geospatial data, and scoping a research project to build a generative model to synthesize missing Sentinel vegetation index images.

images: screen captures of the USDA’s Crop Data Layer, agricultural land use raster data for the entire United States. This data is used as training labels for deep learning to predict crop type.

Skills:
Deep Learning 
Computer Vision
Data Science
2022 - 2024