The opportunities for application of artificial intelligence (AI) and machine learning (ML) to nuclear power for securing the energy future of the U.S. are legion. While applications to the existing fleet are currently underway, it is the advanced reactors operating in the future energy landscape that present the greatest opportunity. AI/ML can potentially transform the use of nuclear power and improve its economic competitiveness. This panel will focus on the staffing problem and the related competitiveness problem, which are already manifest in the current fleet. The challenge is to transform the human from a labor-intensive role to an overseer of technology that operates autonomously, safely, and fits into a dynamic energy network composed of an array of production and storage technologies.

Panelists

  • Thomas Roettger (Northrop Grumman)
  • Raghu Avali (Carnegie Mellon Univ.)
  • Richard Wood (Univ. of Tenn., Knoxville)
  • Ken Thomas (INL)
  • Alison Hahn (Office of Nuclear Energy, DOE)

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