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 Planning, and an MS in Computer Science. Her Bachelor’s degree is in Computer Science and Architecture, from Yale University.


clairego@mit.edu
linkedin
instagram

Waterways / Highways


Experimental final project in computer vision, exploring whether a neural image-to-image translation network can learn relationships between manmade and natural land features. Adapted Pix2Pix (Isola et al. 2016) model was trained to predict basic land use maps given only water features. Results curious but not convincing.

Skills:
Computer Vision

For Yale CPSC.678 Creative AI for Visual Computing, taught by Prof. Julie Dorsey
2019