Nicholas Institute for Environmental Policy Solutions
Simulated network above global map. Image credit pixabay/Gerd Altmann
pixabay/Gerd Altmann

Energy Data Analytics

Big data offers big opportunities to solve our world’s most daunting energy and climate challenges.

That’s why Duke University’s interdisciplinary Energy Data Analytics Lab is developing groundbreaking applications of machine learning techniques and cultivating new data analytics talent for the sector.

Experts affiliated with the lab—including engineers, data scientists, and social scientists—are positioning Duke University as an international leader in the emerging area of energy data analytics.

Among other projects, the lab has pioneered the application of visual object identification and machine learning techniques to satellite imagery for energy resource detection and mapping. One of the lab's long-term objectives is to create a map of global energy infrastructure that can be automatically updated.

Duke's Energy Data Analytics Lab is also creating a pipeline of talented innovators. Projects connected with Duke’s unique Data+ and Bass Connections programs accomplish lab research objectives while deepening undergraduate and graduate students’ research, project management, and communications skills. Thanks to grants from the Alfred P. Sloan Foundation, the lab launched programs for doctoral student fellows and postdoctoral fellows in fall 2018.

Founded in 2014, the Energy Data Analytics Lab is a collaborative effort of the Duke University Nicholas Institute for Energy, Environment & Sustainability (which houses it), the Rhodes Information Initiative at Duke (Rhodes iiD), and the Social Science Research Institute (SSRI).

Issue Experts


Energy Data Resources

Collection of energy data sources and tools for data analysis, filterable by topic and type.

Remote Sensing of Energy Supply

Solar arrays—whether small enough to charge a cellphone or substantial enough to power a community—can be identified and characterized from above using satellite imagery.

Remote Sensing of Transmission & Distribution

Mapping transmission and distribution lines is critical for managing electricity system risk and enabling transitions to sustainable energy.

Remote Sensing of Energy Demand

Satellite and drone imagery can reveal many characteristics of buildings, providing insight into the energy it takes to keep occupants comfortable—and the resulting emissions.

Energy Data Analytics Ph.D. Student Fellows Program

This Ph.D. Fellowship program readies emerging scholars to apply cutting-edge data science techniques to energy and climate challenges and is supported by the Alfred P. Sloan Foundation.

Upscaling Remote Sensing Methodologies to Detect and Map Energy and Climate Resources

Many satellite-based techniques for monitoring energy and climate resources are not able to scale up geographically due to how they’ve been trained. This project explores novel solutions.


The Climate+ program is a full-time, ten-week summer research experience in which small teams of Duke undergraduates and graduate students explore new data-driven approaches addressing climate challenges.