Doctoral students from Carnegie Mellon, UMass Amherst, and Duke land top prizes for energy data analytics research talks
Posted On:Wednesday, Dec 09, 2020 - 9:24 am
Today the Energy Data Analytics Lab at Duke University announced the winners of the Lightning Talks Competition at the Energy Data Analytics Symposium (Dec. 8-9, 2020).
The competition highlights research by emerging scholars in energy data analytics, attracted 21 entries from 12 universities and organizations. Judges assessed participants’ five-minute “lightning talks” on 1) compelling communication of the core ideas and outcomes of the project to an interdisciplinary audience; and 2) innovation and potential for impact of the energy application and data science methodology.
Congratulations to the 2020 winners:
FIRST PRIZE ($500): Priya Donti, Ph.D. student in computer science and public policy at Carnegie Mellon University, for a talk titled, “Inverse Optimal Power Flow: Assessing the Vulnerability of Grid Data”
SECOND PRIZE ($250): Akansha Singh Bansal, Ph.D. student in electrical and computer engineering at the University of Massachusetts Amherst, for a talk titled, “See the Light: Modeling Solar Performance using Multispectral Satellite Data”
THIRD PRIZE ($100): Tongshu Zheng, Ph.D. student in environmental engineering (and Energy Data Analytics Ph.D. Student Fellow) at Duke University, for a talk titled, “Estimating Solar PV Soiling Using a Satellite-Based Remote Sensing Approach”
McKenna Peplinski, Ph.D. student in environmental engineering at the University of Southern California, for a talk titled, “Predicting Changes in Southern California's Residential Electricity Consumption using Machine Learning Models.”
Noman Bashir, Ph.D. student in electrical and computer engineering at the University of Massachusetts Amherst, for a talk titled, “Solar-TK: A Data-driven Toolkit for Solar PV Performance Modeling and Forecasting"
“While these students are still early in their careers, their research has high potential for impact,” remarked Duke University Energy Initiative director Dr. Brian Murray, who served as a judge. “They are using advanced methods in data science to develop fresh approaches to our world’s great energy challenges—and they are adept at communicating their research clearly and succinctly.”
The two-day Energy Data Analytics Symposium (Dec. 8-9, 2020) organized by the Duke University Energy Data Analytics Lab focused on how machine learning and other data science innovations can help transform energy systems to become more accessible, affordable, reliable, and clean. The event, which featured insights from established experts and emerging scholars, was supported by a grant from the Alfred P. Sloan Foundation.
The Energy Data Analytics Lab, which organized the symposium and competition, is a collaboration among the Duke University Energy Initiative (which houses it), the Rhodes Information Initiative at Duke, and the Social Science Research Institute.
(Note: Conclusions reached or positions taken by researchers or other grantees represent the views of the grantees themselves and not those of the Alfred P. Sloan Foundation or its trustees, officers, or staff).
For more information about the competition, contact Trey Gowdy.