Diana Dayoub ’21

Headshot of Diana Dayoub
Major

School of Public and International Affairs

Project Title

Cities, Sensors, Satellites and Sustainability: Mapping Cities and Urban Infrastructure Through Data Science

Presentation Link

View Diana's Presentation

Certificate(s): Finance, Statistics and Machine Learning

I worked with another intern to locate certain types of infrastructure in satellite imagery using a machine learning task called object detection. A database of the locations of different types of infrastructure provides researchers and policymakers with a lot of insight about urban systems, such as sources of high greenhouse gas emissions, or how a given household’s distance from infrastructure services correlates with socioeconomic indicators. By the end of the summer, we were able to identify a methodology that will allow researchers in the lab to locate infrastructure in satellite imagery. This internship was my introduction to machine learning in general and object detection in particular. It taught me everything from technical deep-learning skills, to structuring a broad, demanding task and collaborating to tackle multifaceted and technically challenging problems. I will continue to work with Professor Ramaswami’s lab throughout the year and hopefully use the data I obtain for my thesis research.

 



Internship Year

2020

Project Category

Urban Systems and Planning for a Sustainable Future

Organization(s)

Sustainable Urban Infrastructure Systems Lab, Department of Civil and Environmental Engineering, Princeton University

Mentor(s)

Anu Ramaswami, Sanjay Swani ’87 Professor of India Studies, Professor of Civil and Environmental Engineering and the High Meadows Environmental Institute; Dana Boyer, Research and Development Manager, High Meadows Environmental Institute; Michael Milnar, Graduate Research Assistant, Sustainable Healthy Cities Network