NC State Nuclear Engineering holds an annual Distinguished Executive Lecture. It is an opportunity to engage with thought leaders in the nuclear science and technology. Dr. Kathryn D. Huff will be the speaker on January 26.
Clean Energy and Nuclear Innovation – a path forward
Dr. Kathryn Huff, Assistant Secretary for Nuclear Energy
U.S. Department of Energy, Office of Nuclear Energy
Thursday, January 26 @ 4:30 p.m.
Withers 232A, 101 Lampe Drive
North Campus, NC State University
Details & RSVP, click here (in-person & virtual)
Dr. Kathryn Huff leads the Office of Nuclear Energy as the Assistant Secretary. Prior to her current role, she served as a Senior Advisor in the Office of the Secretary. Dr. Huff also led the office as the Principal Deputy Assistant Secretary for Nuclear Energy. Before joining the Department of Energy, she was an Assistant Professor in the Department of Nuclear, Plasma, and Radiological Engineering at the University of Illinois at Urbana-Champaign where she led the Advanced Reactors and Fuel Cycles Research Group. She was also a Blue Waters Assistant Professor with the National Center for Supercomputing Applications. She was previously a Postdoctoral Fellow in both the Nuclear Science and Security Consortium and the Berkeley Institute for Data Science at the University of California – Berkeley. She received her PhD in Nuclear Engineering from the University of Wisconsin-Madison in 2013 and her undergraduate degree in Physics from the University of Chicago. Her research focused on modeling and simulation of advanced nuclear reactors and fuel cycles.
She is an active member of the American Nuclear Society, a past Chair of the Nuclear Nonproliferation and Policy Division as well as the Fuel Cycle and Waste Management Division, and recipient of both the Young Member Excellence and Mary Jane Oestmann Professional Women’s Achievement awards. Through leadership within Software Carpentry, SciPy, the Hacker Within, and the Journal of Open Source Software she also advocates for best practices in open, reproducible scientific computing.