How can machine learning and data science tools improve our understanding of energy systems and manage them to be more accessible, affordable, reliable, and clean? This single-track symposium will explore cutting-edge approaches addressing this question, highlighting the work of established experts as well as emerging scholars in the field.
In particular, the symposium will examine how data science and machine learning are driving innovation in areas including:
- Remote sensing of energy resources and infrastructure;
- Energy systems modeling;
- Energy consumption end uses;
- Energy and climate change; and
- Energy access.
Note: This even was originally planned to be held in May 2020. The Symposium is moving to an all-online format in December 2020. This webpage will be updated frequently as changes are confirmed.
Dr. Mario Berges, Carnegie Mellon University
- Professor, Civil, and Environmental Engineering
- Director, Intelligent Infrastructure Research Lab
Dr. Kyle Bradbury, Duke University
- Managing Director, Energy Data Analytics Lab
- Lecturing Fellow, Electrical and Computer Engineering
Dr. Heather Couture, Pixel Scientia Labs
- Founder, Pixel Scientia Labs
- Machine Learning Consultant & Researcher
Dr. Dylan Harrison-Atlas, National Renewable Energy Laboratory
- Senior Data Scientist, Geospatial Data Science Group, Strategic Energy Analysis Center
Dr. Brian Min, University of Michigan
- Associate Professor, Political Science
- Faculty Affiliate for Energy Institute
Martha Morrissey, Development Seed
- Machine Learning Engineer
Dr. Elisabeth Moyer, University of Chicago
- Associate Professor, Atmospheric Science
- Co-Principal Investigator, Center for Robust Decision-making on Climate and Energy Policy
Dr. Zoltan Nagy, University of Texas at Austin
- Assistant Professor, Civil, Architectural, and Environmental Engineering
- Director, Intelligent Environments Laboratory
John Pressley and Dylan Lustig, Duke Energy Corporation
- Director, Information Management Solutions, Digital Transformation and Lead Analyst, Digital Transformation
Dr. Brian Prest, Resources for the Future
Dr. Edward Rubin, University of Oregon
- Assistant Professor, Economics
Dr. Cynthia Rudin, Duke University
- Professor, Computer Science
- Principal Investigator, Prediction Analysis Lab
More details coming soon!
The symposium will also highlight research by two interdisciplinary cohorts of doctoral students who are part of Duke University's Energy Data Analytics Ph.D. Student Fellows Program, funded by the Alfred P. Sloan Foundation.
Dec. 8 (Tuesday, 1:00-5:00pm ET) and 9 (Wednesday, 1:00-4:30pm ET)
More details and an agenda are coming soon.
Form and Format of Presentations
- There will be a mixture of live and pre-recorded content, all presented remotely through interactive virtual conference software.
- Dissemination: To increase the impact of their work, speaker presentations will be recorded and videos will be made available online after the symposium.
Research Video Competition
Eligible Symposium participants are invited to participate in the Energy Data Analytics Research Video competition. These 5-minute lightning talk videos will be pre-recorded by the author and made available in advance of the Symposium.
For determining the winners of the competition, the review committee will select the top three videos based on the following criteria:
- Compelling communication of the core ideas and outcomes of the project in the video to an interdisciplinary audience
- Innovation and potential for impact of the energy application and data science methodology
Recognition and Awards for Top 3 Videos:
- Awards: 1st Place: $500, 2nd Place: $250, 3rd Place: $100
- Videos presented as part of a plenary session during the Symposium
- Recognition on the Symposium website
- DEADLINE: Videos due by Friday, November 20. Send videos by file transfer link by to email@example.com. Upon request, a file transfer option via Box can be provided by Duke University. Contact Trey Gowdy with any questions.
- .MP4, .MOV, or .WMV file formats preferred.
- Videos must be no more than 5 minutes (longer videos will be considered ineligible for the competition).
- Videos will be posted online, ensure no copyrighted materials (e.g. music or images) are used without permission. Use of copyrighted materials will render your submission ineligible for inclusion in the competition and the Symposium.
- Please provide on-screen citations for any statistics, quotes, or other similar information.
Viewing and Discussion:
- Videos will be made available for asynchronous viewing before the Symposium. We encourage all participants to view each of your colleagues’ research videos.
- Using the networking time during the Symposium, we aim for these videos to be a means to start conversations with fellow attendees. We aim for the Symposium to build a community. We will also provide a means for asynchronous Q&A.
Previously registered participants and speakers will receive more information by email.
Organizers and Funding
The symposium is being organized by Dr. Kyle Bradbury, Dr. Jordan Malof, Dr. Brian Murray, Dr. Billy Pizer, and Dr. Cynthia Rudin at Duke University's Energy Data Analytics Lab, a collaborative effort of the Duke University Energy Initiative (which houses it), the Rhodes Information Initiative at Duke, and the Social Science Research Institute. Funding support for the workshop is provided by a grant from the Alfred P. Sloan Foundation.
Contact Trey Gowdy at firstname.lastname@example.org.