Providing education, research, problem-solving, and service in nuclear science and engineering

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RadLab

The RadLab at The University of Texas at Austin focuses on research using radiation and radioactivity to improve security and quality of life.

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Reactor

The NETL reactor, designed by General Atomics, is a TRIGA Mark II nuclear research reactor. The NETL is the newest of the current fleet of U.S. university reactors.

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Robotics

The Nuclear and Applied Robotics Group is an interdisciplinary research group whose mission is to develop and deploy advanced robotics in hazardous environments in order to minimize risk for the human operator.

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$20M+

In funding for molten salt reactor development

60+

Graduate students

$1.7M

Research expenditures per tenured/tenure-track faculty in FY23

News

NRE Student, Braden Pecora, awarded inaugural KBH Computation Energy Fellowship

Braden Pecora, KBH Computation Energy Fellowship Award 2026

Nuclear and Radiation Engineering graduate student Braden Pecora has been selected as the 2026–27 Kay Bailey Hutchison (KBH) Computational Energy Fellow, a joint fellowship from the Oden Institute for Computational Engineering and Sciences and the KBH Energy Center at UT Austin.

The fellowship recognizes an outstanding Oden Institute graduate student or postdoctoral fellow who contributes computational science expertise to the educational programming of the KBH Energy Center's Energy Studies Minor. 

Register for event with Commissioner David Wright, March 31

Join the UT Nuclear Niche for an in-person fireside chat with Commissioner David Wright of the Nuclear Regulatory Commission. Use the QR code below or this link to register

📍 Rowling 5.210
🗓 Tuesday, March 31, 2026
⏰ 1:30–3:00 PM

🍭 Light bites provided

New Publication on the economic viability of nuclear power in Texas

Current PhD student Ivy Seidel published the peer-reviewed paper, Investigating nuclear energy viability in Texas with decision making model GenX, in the journal Energy Economics. This paper focuses on the analysis of the economic viability of Nuclear Power in Texas. Seidel utilized open source capacity expansion model GenX to weigh the cost of unserved energy against the cost of implementing nuclear power in the face of electricity demand growth Texas. ERCOT is expected to experience a dramatic increase in the number of data centers being constructed due to the favorable economic landscape of the state, this would greatly impact industrial power draw and need to be accounted for in the coming years. A sharp rise in power demand along with expected population growth is predicted to cause a near doubling of the average electricity demand in Texas by 2030.

Register for Fireside Chat with Isabelle Boemeke March 24th

Join the UT Nuclear Niche for an in-person fireside chat with Isabelle Boemeke on Advocacy in the Last Nuclear Renaissance. Use the QR code below or this link to register

📍 Rowling 5.210
🗓 Tuesday, March 24, 2026
⏰ 5:30–7:00 PM

New Publication by Dr. Seo

Dr. Jeongwon Seo's paper, Softmax-Based Deep Neural Network in Regression, was recently published in the Journal of VVUQ. While traditional AI regression models are great at giving a single "average" answer, they often struggle with the messy, unpredictable nature of real-world data. 

To overcome this, Dr. Seo's approach borrows a clever tactic from classification: by breaking continuous outputs into discrete 'bins', the model can predict not just a single number, but the entire landscape of probabilities.