M-PRISM research group

News

Awards, talks, papers and other milestones from the group, newest first.

2026

  • · ANS Winter Conference, Phoenix

    PhD student Samah Balouza and undergraduate Jake LaFore each lead a paper on the JSI TRIGA Mark-II reactor at the 2026 ANS Winter Conference & Expo in Phoenix, Arizona.

    • Comparing Fission Matrix Approaches using a JSI TRIGA Mark-II Reactor ModelSamah Balouza
    • Evaluation of the Effect of Control Rod Positioning on One-Group Effective Nuclear Data for Ex-Core Flux Reconstruction in the JSI TRIGA Mark-II ReactorJake LaFore
    Banner of the 2026 ANS Winter Conference & Expo: November 15–18, Phoenix, AZ, with the theme Going Critical: Creating a Durable Nuclear Resurgence
  • · RERTR-2026, Osaka

    Advances in Open-Source Research Reactor Design with OpenMC and ADDER for Proliferation Resistance Optimization

    Collaborators from Argonne National Laboratory will present this work by undergraduate Thomas McCoy at RERTR-2026, the 46th International Meeting on Reduced Enrichment for Research and Test Reactors in Osaka, Japan: in Panel 1 and in the evening poster session.

    Cover of the RERTR-2026 program: 46th International Meeting on Reduced Enrichment for Research and Test Reactors, October 26-29, 2026, Osaka, Japan
  • · ME faculty meeting, Mines

    The postdoc in my terminal: agentic AI across a real research workflow

    I spoke to the Mechanical Engineering faculty, at a session hosted by the department AI Committee, about using an AI agent (Claude Code) in research. Over four weeks it worked with me on three projects: a paper, a C++ simulation engine, and a study. Two agents ran live demos during the talk.

    Title slide of the talk The postdoc in my terminal: agentic AI across a real research workflow, by Valerio Mascolino, October 6, 2026, on the Colorado School of Mines template
  • · Mines Undergraduate Research Symposium

    Undergraduates Jake LaFore, Thomas McCoy, and Daris Paine presented posters at the fifth annual Fall Undergraduate Research Symposium at Colorado School of Mines, held in the CoorsTek Atrium.

    • Computational Analyses for Validation and Acceleration of a Machine Learning Approach to Neutron Flux Reconstruction in Next-Generation Nuclear ReactorsJake LaFore
    • Advances in Open-Source Research Reactor Design with OpenMC and ADDER for Proliferation Resistance OptimizationThomas McCoy
    • Neural Network Prediction of the Fission MatrixDaris Paine
    Colorado School of Mines Undergraduate Research Symposium logo, with the word Research filled with images of student projects
  • · UPCC 2026, CU Boulder

    Computational Analyses for Validation and Acceleration of a Machine Learning Approach to Neutron Flux Reconstruction in Next-Generation Nuclear Reactors

    Undergraduate Jake LaFore won Best Speaker in High-Energy Physics for this talk at the Undergraduate Physics Conference of Colorado (UPCC 2026), held in Duane Physics & Astrophysics at CU Boulder.

    Jake LaFore holds his Best Speaker certificate between UPCC co-directors Zachary Larter and Jeremy Goodkin, in front of the award slide
    Photo: UPCC 2026, by Tab Rodriguez.
  • · Argonne National Laboratory

    Undergraduate Thomas McCoy spent the summer as a Research Aide in the Research and Test Reactors Department at Argonne National Laboratory, building an OpenMC model of the IAEA TECDOC-643 research reactor core.

    Argonne National Laboratory logo
  • · ANS Annual Conference, Denver

    Neural Network-Enabled Thermal Feedback Modeling in the Fission Matrix Method

    Undergraduate Daris Paine presented this work in the Reactor Physics Method session of the 2026 ANS Annual Conference in Denver. A neural network learns how temperature changes the fission matrix, and its k-eff error falls steadily as the training set grows.

    Plot of the neural network's k-eff relative error against dataset size: the error falls from about 1,200 pcm with 200 fission-matrix libraries to about 240 pcm with 1,700, following a power-law fit
    Fig. 4 of the paper: validation error against the number of fission-matrix libraries used for training.