Lindy Zeng ’18


Computer Science

Project Title

Interactive Machine Learning to Map African Crop Fields

Presentation Link

View Lindy's Presentation

This summer, I interned on Princeton’s Mapping Africa team, which seeks to use remote sensing technology, the Internet, computer vision, and machine learning to gain a better understanding of the distribution and extent of Africa’s farmland. My specific project was to connect Mapping Africa’s existing human intelligence and machine learning processes by creating a web mapping application. During the project, I was exposed to many new programming languages and free and open-source software (FOSS) for Geographic Information Systems (GIS). I also gained a better understanding of Africa’s food insecurity issues and how Mapping Africa’s goal of creating a more accurate map of farmland in Africa will contribute to the world’s understanding of the issues regarding the ecological and socioeconomic sustainability of agriculture in Africa. Most importantly, I witnessed the impact that computers, technology, and human beings can make when combined, and I am inspired to use it to help solve more societal problems.

Internship Year


Project Category



Caylor Ecohydrology Lab, Princeton University, Princeton, NJ


Lyndon Estes, Associate Research Scholar, Woodrow Wilson School and the Program in Science, Technology and the Environment