UNC PhD students Katherine Burley, Ying Yu and Beth Brown, have been selected for the Energy Data Analytics PhD Student Fellows program at Duke University. All three awardees are interested in energy and environmental policy research and are involved with DDL or Dr. Angel Hsu.
The prestigious Energy Data Analytics PhD Student Fellows program was established in 2018 to give next-generation scholars the skills to deftly use data in pursuit of accessible, affordable, reliable, and clean energy systems. Recent growth of energy data availability and improvements in data science techniques have created new opportunities to solve pressing energy challenges. The fellowship gives PhD students the opportunity to explore these new opportunities using cutting-edge technologies through a summer research project.
Open to doctoral students at universities across North Carolina, the fellowship program is housed by the Nicholas Institute for Energy, Environment & Sustainability at Duke and funded by a grant from the Alfred P. Sloan Foundation.
Each student in the program receives $1500 in research funds for computation and professional development and funding for 3 months of support in the summer. Additionally, fellows attend regular mentorship and training workshops to improve their interdisciplinary communication and data science tools in relation to energy systems.
We chatted with all three upcoming fellows to get a better idea of how this program fits into their research interests and what they are most looking forward to.
Katherine Burley
“My time at DDL has really helped me grow in my analytical and research skills and expand my understanding of environmental and climate change issues. I think [the fellowship] will be a great opportunity for all the fellows to share knowledge across the Triangle and further develop our analytical skills to address a variety of issues related to energy.”
Katherine is a research assistant for DDL working towards a Ph.D. in Public Policy at UNC under the advisement of DDL Director Dr. Hsu. Her research interests lie at the intersection of subnational policy responses to climate change, utility regulation, and the renewable energy transition. In her fellowship research project, Katherine will explore the relationship between neighborhood demographics and electricity generation to create a new metric: Restoration Equity, which quantifies the level of inequality in electricity restoration for low-income and marginalized communities. Katherine is excited to improve her analytical skills and collaborate with other students at UNC, NC State, and Duke.
Ying Yu
“I am most excited about the opportunity to exchange and share knowledge with peers and experts in the field of energy data analytics. I believe my project on improving energy data is of great significance and relevance to both academia and policymakers, and I am eager to take advantage of the platform.”
Ying collaborates with DDL to predict heat maps and heat disparities among sociodemographic groups using integrated assessment modeling (IAM) and is pursuing a PhD in Environmental Sciences and Engineering in the Gillings School of Global Public Health at UNC-Chapel Hill, under the advisement of DDL collaborator Professor Noah Kittner. Ying is interested in using applied microeconomics methods to answer research questions related to climate and energy. Her fellowship research project aims to accurately estimate the relationship between historical temperature fluctuations and energy inequity using the spatial and temporal resolution of existing energy data. In this pursuit, her project will build off of past DDL research and inform future DDL research related to urban heat disparities.
Beth Brown
“I’m excited to build specialized knowledge on energy and environmental topics, as well as remote sensing and machine learning.”
Beth is pursuing a PhD in Public Policy under the supervision of DDL Director Dr. Hsu. Her research interests are at the intersection of development economics and environmental policy, with a focus in improving energy access and environmental quality for low-income populations. During the fellowship this summer, Beth will develop a machine learning model to design efficient energy distribution networks for mini-grid planning in remote areas. Beth is excited to get connected with more mentors in her field and to continue her work with Dr. Hsu.
DDL is so proud of our 2023 Energy Data Analytics PhD Student Fellows. We are also excited for the opportunity to lift up a group of such smart, talented women in the data science field.
We can’t wait to see the outcomes of their research projects this summer.
For the most up-to-date information about DDL research, check out our projects and publications pages.
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