Nicholas Institute for Environmental Policy Solutions

Energy Mix: Networking Reception for the Energy Data Analytics Symposium

Date and Time
Thursday, October 26, 2023 - 4:30 p.m. to 6:30 p.m.
Location
Duke University’s Fuqua School of Business, Kirby Winter Garden 100 Fuqua Drive Durham, NC 27708
Energy Mix: Networking Reception for the Energy Data Analytics Symposium

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Join a networking reception to plug in with experts from academia, industry, and the public sector who will be attending the two-day Energy Data Analytics Symposium at Duke University.

The Energy Mix is open to all members of the Duke community; energy professionals in the Triangle; and students, faculty, and staff from other area universities. You’ll be able to network with energy and data science experts and emerging professionals engaged in data-driven energy research around the country.

The reception will feature remarks from Jerome Lynch, Vinik Dean of Engineering at the Duke University Pratt School of Engineering. Lynch is expected to speak around 5:30 p.m.

Food and drinks will be provided. PLEASE NOTE: Anyone who wants an alcoholic beverage must show ID proving that they are at least 21 years old.

** Attendees already registered for the symposium do not need to re-register separately for this reception. **

About the Hosts

The reception will be hosted by the Energy Data Analytics Lab at Duke University's Nicholas Institute for Energy, Environment & Sustainability and the Energy Analysis and Policy (EAP) Program at the University of Wisconsin-Madison. The Energy Data Analytics Lab and EAP are also organizing the symposium, with funding support provided by the Alfred P. Sloan Foundation and NASA.

About the Symposium

The Energy Data Analytics Symposium is an in-person event that will explore leading approaches to how data science tools, including artificial intelligence, can help us make energy systems more accessible, affordable, reliable, and environmentally sustainable.

In particular, the symposium will examine how data science and machine learning are driving innovation in these areas:

  • Remote sensing for energy and climate data;
  • Ethics and social responsibility for energy and climate data analytics;
  • Energy systems modeling; and
  • Energy access.

The symposium is full. Anyone interested in attending is welcome to register for a waitlist.