Welcome
Ian Kolaja is a nuclear engineer focused on advanced reactor operation and fuel measurement. He earned his PhD in Nuclear Engineering from UC Berkeley, with a designated emphasis in Computational and Data Science and Engineering. He also completed his undergraduate degree at Berkeley after transferring from Fullerton College. Ian is a strong advocate for transfer students and for those impacted by the foster youth system.
Research
Ian's dissertation addressed key challenges in operating and monitoring pebble bed reactors (PBRs), with extensions to molten salt reactors (MSRs). His work combined high-fidelity modeling, bent crystal diffraction (BCD) spectroscopy, and machine learning.
Fuel pebbles discharged from PBRs must be measured quickly under intense radiation, conditions where conventional gamma spectroscopy struggles. Ian designed BCD spectrometers—devices widely used in astrophysics but never before applied to PBRs—that act as energy filters for gamma rays. Coupled with machine learning, these spectrometers enabled accurate prediction of pebble properties such as burnup, residence time, and fluence
He also developed long-short term memory (LSTM) models to connect these measurements with operation history, predicting reactivity and flux/power distributions over time. This approach allows operators to forecast reactor behavior and optimize startup sequences, reducing the time to equilibrium.
For MSRs, Ian demonstrated that the same BCD spectroscopy methods could isolate key isotopes like Np-239, enabling real-time tracking of plutonium production for safeguards applications.
Industry Experience
Before his PhD, Ian worked at Kairos Power, where he was the first developer of the Kairos Power Advanced Core Simulator (KPACS). This tool supported equilibrium core studies for the company’s generic fluoride-salt-cooled high temperature reactor (gFHR) benchmark and contributed to the early design of KP-Hermes 1.
Outside of Nuclear
Ian has a wide range of creative pursuits including music production and filmmaking. Before pursuing science in community college, he wanted to be a film director. He participated and won awards at a handful of student film festivals in Southern California. He also recently has released his first EP, a collection of indie pop songs.
Publications
I. Kolaja et al., “Machine Learning Prediction of Pebble History in Pebble Bed Reactors,” in Proceedings of the International Conference on Physics of Reactors (PHYSOR 2024), Apr. 2024, pp. 1437-1446. doi: 10.13182/PHYSOR24-43890.
N. Satvat et al., “Neutronics, thermal-hydraulics, and multi-physics benchmark models for a generic pebble-bed fluoride-salt-cooled high temperature reactor (FHR),” Nuclear Engineering and Design, vol. 384, no. C, Nov. 2021, doi: 10.1016/j.nucengdes.2021.111461.
J. M. Gates et al., “First Direct Measurements of Superheavy-Element Mass Numbers,” Phys. Rev. Lett., vol. 121, no. 22, p. 222501, Nov. 2018, doi: 10.1103/PhysRevLett.121.222501.