News - Energy Data Analytics
Joseph DeCarolis, administrator of the U.S. Energy Information Administration, recently delivered the keynote presentation at the 2023 Energy Data Analytics Symposium.
The winners from the University of Wisconsin-Madison, University of North Carolina at Chapel Hill and University of Montana were among two dozen emerging scholars and energy professionals from around the country who submitted five-minute lightning talk videos on their own work or a big idea.
The new Office of Climate and Sustainability brings together several of Duke University's climate, energy, and environmental assets—including the Nicholas Institute—to help advance the mission of the Duke Climate Commitment.
The Energy Data Analytics Ph.D. Student Fellows program is designed to prepare the next generation of scholars to deftly wield data in pursuit of accessible, affordable, reliable and clean energy systems. The 2023 group of students will conduct research on topics including renewable energy, energy forecasting, efficient lightning, coal pollution, energy equity and extreme weather impacts on energy systems.
Kyle Bradbury spoke to Duke's student newspaper The Chronicle about the second summer of Climate+, a program for students interested in applying data science techniques to climate research projects.
The Rhodes Information Initiative at Duke (Rhodes iiD), in partnership with the Nicholas Institute for Energy, Environment & Sustainability is now accepting student applications for this summer’s Climate+ projects. Climate+ is a vertical within Rhodes iiD’s Data+ program, a full-time, ten-week summer research experience for Duke students of all class years and majors.
This year, six emerging scholars from Duke University, North Carolina State University, and the University of North Carolina at Chapel Hill will take part in a unique Duke-based program aimed at preparing energy and climate innovators to make an impact.
One of Duke University’s signature summer education programs is expanding student opportunities to apply cutting-edge data science methods to climate challenges.
Dive into this foundational video on unsupervised learning by Dr. Jordan Malof. This talk introduces common unsupervised learning techniques and how they can be applied to energy challenges. You'll hear about mixed clustering, dimensionality reduction, and more!