Vijay Modi

1. Building energy systems are necessary to reduce greenhouse gas emissions, but energy usage within a building also has economic implications for building owners, tenants and utilities. How cost-effective changes to energy systems intersect with considerations of affordability, incomes and needs of residents is poorly understood. Yet this is essential to ensure a just transition in building energy. The Quadracci Sustainable Engineering Lab (QSEL) is seeking an intern who would work with multiple sources of granular data to discern systematic trends and assist in identifying possible solutions to energy's environmental and economic impact. Some experience with Python or R is expected, particularly working with data. During the internship, you may also gain some experience with QGIS mapping software, depending on project needs.

2. The Quadracci Sustainable Engineering Lab (QSEL) is using a combination of geospatial / GIS and other data to help understand agricultural practices and plan investments to improve agriculture in Sub Saharan Africa. QSEL is seeking an intern to help review and analyze spatial and satellite image data, perhaps in combination with other sources of information such as tabular data and reports on economic and agricultural factors. Preference will be given for applicants with experience using GIS software (QGIS, ArcGIS) as well as working with satellite imagery. Experience with Python, Linux, and/or data analysis, is also a plus.

For more information, see the Columbia World Project "Using Data to Catalyze Energy Investments": https://worldprojects.columbia.edu/projects/active-projects/using-data-catalyze-energy-investments

3. The Quadracci Sustainable Engineering Lab (QSEL) is using computer vision to encourage investment in agriculture in the developing world. By collecting and analyzing street view style data we aim to provide unbiased labeled datasets that show the demand for irrigation technologies. Help us to field test stereo vision equipment, gather data locally, and process data collected in Sub Saharan Africa to geolocate potentially irrigated farmland in rural landscapes.

Preference towards experience with Python, Linux, and Data Analysis, no experience with computer vision required.