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Jordan Stomps

PhD Candidate

Oak Ridge National Laboratory
1 Bethel Valley Road
Oak Ridge, TN 37831

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Jordan’s research focuses on machine learning applications to nuclear nonproliferation. In particular, he is using gamma radiation measurements collected for the NNSA NA-22 Multi-Informatics for Nuclear Operations Scenarios testbed at Oak Ridge National Laboratory to train models capable of detecting shielded radiological material transfers. State-of-the-art artificial intelligence techniques require large volumes of labeled data to train a successful model. Characterizing radiation data often involves manual analysis by subject-matter experts which is time consuming, resource intensive, and unfeasible for leveraging machine learning. Jordan is addressing this by using semi-supervised machine learning to utilize labeled and unlabeled radiation measurements to design models that can be used for more informed decisions and resource efficiency in nuclear security. His research is supported by the NNSA Consortium for Enabling Technology and Innovation (ETI) under the computer and engineering sciences for nonproliferation thrust. Originally from Detroit, Jordan spends his free time gardening and cooking with his wife, daughter, and dog.

For more information on recent research, please review this publication.

Research Interests

  • Semi-Supervised Machine Learning
  • Nuclear Nonproliferation
  • Artificial Intelligence
  • Data Science and Analysis
  • Fuel Cycle Analysis
  • Scientific Computing
  • Radiation Detection
  • Anomaly Detection


  • University of Wisconsin, Madison, WI [PhD. Graduate Student, Nuclear Engineering & Engineering Physics]
  • University of Wisconsin, Madison, WI [M.S. Nuclear Engineering & Engineering Physics, 2021]
  • Michigan State University, East Lansing, MI [BS Physics, 2019]

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