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Research Directory

Explore our lab's publications and current research projects across our three main focus areas: Reactors, Controls, and Computing. Our interdisciplinary approach combines nuclear engineering with advanced computational methods to solve complex challenges.

Directory last updated

08-11-2025

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Showing 38 items

A Bayesian ensemble approach for improved sustainable aviation fuel modeling
Publication

A Bayesian ensemble approach for improved sustainable aviation fuel modeling

Mohammed I. Radaideh, Majdi I. Radaideh, Angela Violi

Energy Conversion and Management: X

2025

Opening the AI black-box: Symbolic regression with Kolmogorov–Arnold Networks for advanced energy applications
Publication

Opening the AI black-box: Symbolic regression with Kolmogorov–Arnold Networks for advanced energy applications

Nataly R. Panczyk, Omer F. Erdem, Majdi I. Radaideh

Energy and AI

2025

Nuclear microreactor transient and load-following control with deep reinforcement learning
Publication

Nuclear microreactor transient and load-following control with deep reinforcement learning

Leo Tunkle, Kamal Abdulraheem, Linyu Lin, et al.

Energy Conversion and Management: X

2025

Nuclear microreactorMulti-agent RL (MARL)Reactivity control
Multi-objective combinatorial methodology for nuclear reactor site assessment: A case study for the United States
Publication

Multi-objective combinatorial methodology for nuclear reactor site assessment: A case study for the United States

Omer Erdem, Kevin Daley, Gabrielle Hoelzle, et al.

Energy Conversion and Management: X

2025

Multi-objective combinatorial methodologyNuclear power plantNeural network
Efficient sampling of polycyclic aromatic compounds for free energy predictions through active learning
Publication

Efficient sampling of polycyclic aromatic compounds for free energy predictions through active learning

Mohammed I. Radaideh, Matt Raymond, Paolo Elvati, et al.

Energy and AI

2025

Polycyclic Aromatic Compounds (PACs)Free energy predictionsActive learning
Fairness and social bias quantification in Large Language Models for sentiment analysis
Publication

Fairness and social bias quantification in Large Language Models for sentiment analysis

Mohammed I. Radaideh, O. Hwang Kwon, Majdi I. Radaideh

Knowledge-Based Systems

2025

Large Language Models (LLM)Natural Language Processing (NLP)Sentiment Analysis
Data efficiency assessment of generative adversarial networks in energy applications
Publication

Data efficiency assessment of generative adversarial networks in energy applications

Umme Mahbuba Nabila, Linyu Lin, Xingang Zhao, et al.

Energy and AI

2025

Generative adversarial networksEnergy demand forecastingSynthetic data
A load following reactivity control system for nuclear microreactors
Publication

A load following reactivity control system for nuclear microreactors

Kamal K. Abdulraheem, Sooyoung Choi, Qicang Shen, et al.

Progress in Nuclear Energy

2025

MicroreactorSliding mode control systemNonlinear model predictive control
Multistep Criticality Search and Power Shaping in Nuclear Microreactors with Deep Reinforcement Learning
Publication

Multistep Criticality Search and Power Shaping in Nuclear Microreactors with Deep Reinforcement Learning

Majdi I. Radaideh, Leo Tunkle, Dean Price, et al.

Nuclear Science and Engineering

2025

Multistep Criticality SearchPower ShapingReinforcement Learning
pyMAISE: A Python platform for automatic machine learning and accelerated development for nuclear power applications
Publication

pyMAISE: A Python platform for automatic machine learning and accelerated development for nuclear power applications

Patrick A. Myers, Nataly Panczyk, Shashank Chidige, et al.

Progress in Nuclear Energy

2024

Machine learningNuclear powerFeedforward neural networks
A comparative analysis of text-to-image generative AI models in scientific contexts: a case study on nuclear power
Publication

A comparative analysis of text-to-image generative AI models in scientific contexts: a case study on nuclear power

Veda Joynt, Jacob Cooper, Naman Bhargava, et al.

Scientific Reports

2024

Generative AINuclear powerText-to-image
Multiphysics Modeling of Heat Pipe Microreactor with Critical Control Drum Position Search
Publication

Multiphysics Modeling of Heat Pipe Microreactor with Critical Control Drum Position Search

Dean Price, Nathan Roskoff, Majdi I. Radaideh, et al.

Nuclear Science and Engineering

2024

Multiphysics ModelingHeat Pipe MicroreactorCritical Control Drum Position Search
Distance preserving machine learning for uncertainty aware accelerator capacitance predictions
Publication

Distance preserving machine learning for uncertainty aware accelerator capacitance predictions

Steven Goldenberg, Malachi Schram, Kishansingh Rajput, et al.

Machine Learning: Science and Technology

2024

Gaussian processHigh Voltage Converter ModulatorsDeep neural networks
Sentiment analysis of the United States public support of nuclear power on social media using large language models
Publication

Sentiment analysis of the United States public support of nuclear power on social media using large language models

O. Hwang Kwon, Katie Vu, Naman Bhargava, et al.

Renewable and Sustainable Energy Reviews

2024

Large language modelsSentiment AnalysisNuclear power
Simplified matching pursuits applied to 3D nuclear reactor temperature distribution construction
Publication

Simplified matching pursuits applied to 3D nuclear reactor temperature distribution construction

Dean Price, Majdi I. Radaideh, Brendan Kochunas

Applied Mathematical Modelling

2024

Nuclear reactor temperature distributionMatching pursuits-based methodNuclear microreactor economic viability
Thermal Modeling of an eVinci™-like heat pipe microreactor using OpenFOAM
Publication

Thermal Modeling of an eVinci™-like heat pipe microreactor using OpenFOAM

Dean Price, Nathan Roskoff, Majdi I. Radaideh, et al.

Nuclear Engineering and Design

2023

Thermal ModelingHeat Pipe MicroreactorOpenFOAM
Operational data for fault prognosis in particle accelerators with machine learning
Publication

Operational data for fault prognosis in particle accelerators with machine learning

Majdi I. Radaideh, Chris Pappas, Mark Wezensky, et al.

Data in Brief

2023

Radio-frequency test facilityParticle acceleratorsMagnetic flux compensation
Multi-module-based CVAE to predict HVCM faults in the SNS accelerator
Publication

Multi-module-based CVAE to predict HVCM faults in the SNS accelerator

Yasir Alanazi, Malachi Schram, Kishansingh Rajput, et al.

Machine Learning with Applications

2023

Conditional Variational AutoencoderHigh Voltage Converter ModulatorsArtificial Neural Network
NEORL: NeuroEvolution Optimization with Reinforcement Learning—Applications to carbon-free energy systems
Publication

NEORL: NeuroEvolution Optimization with Reinforcement Learning—Applications to carbon-free energy systems

Majdi I. Radaideh, Katelin Du, Paul Seurin, et al.

Nuclear Engineering and Design

2023

NeuroEvolution OptimizationReinforcement LearningCarbon-free energy systems
Early Fault Detection in Particle Accelerator Power Electronics Using Ensemble Learning
Publication

Early Fault Detection in Particle Accelerator Power Electronics Using Ensemble Learning

Majdi I. Radaideh, Chris Pappas, Mark Wezensky, et al.

International Journal of Prognostics and Health Management

2023

Early Fault DetectionEnsemble LearningSpallation Neutron Source
Application of Convolutional and Feedforward Neural Networks for Fault Detection in Particle Accelerator Power Systems
Publication

Application of Convolutional and Feedforward Neural Networks for Fault Detection in Particle Accelerator Power Systems

Majdi Radaideh, Chris Pappas, Pradeep Ramuhalli, et al.

Annual Conference of the PHM Society

2022

Feedforward neural networksHigh Voltage Converter ModulatorsParticle Accelerator Power Systems
Animorphic ensemble optimization: a large-scale island model
Publication

Animorphic ensemble optimization: a large-scale island model

Dean Price, Majdi I. Radaideh

Neural Computing and Applications

2022

Animorphic ensemble optimizationSwarm algorithmsQuantitative diagnostics metrics
PESA: Prioritized experience replay for parallel hybrid evolutionary and swarm algorithms - Application to nuclear fuel
Publication

PESA: Prioritized experience replay for parallel hybrid evolutionary and swarm algorithms - Application to nuclear fuel

Majdi I. Radaideh, Koroush Shirvan

Nuclear Engineering and Technology

2022

Nuclear fuelParticle swarm optimizationParallel computing
Time series anomaly detection in power electronics signals with recurrent and ConvLSTM autoencoders
Publication

Time series anomaly detection in power electronics signals with recurrent and ConvLSTM autoencoders

Majdi I. Radaideh, Chris Pappas, Jared Walden, et al.

Digital Signal Processing

2022

High voltage converter modulatorLong-short term memoryRecurrent AutoEncoders
Real electronic signal data from particle accelerator power systems for machine learning anomaly detection
Publication

Real electronic signal data from particle accelerator power systems for machine learning anomaly detection

Majdi I. Radaideh, Chris Pappas, Sarah Cousineau

Data in Brief

2022

Electronic signalsHigh Voltage Converter ModulatorsInsulated-gate bipolar transistor
Model calibration of the liquid mercury spallation target using evolutionary neural networks and sparse polynomial expansions
Publication

Model calibration of the liquid mercury spallation target using evolutionary neural networks and sparse polynomial expansions

Majdi I. Radaideh, Hoang Tran, Lianshan Lin, et al.

Nuclear Instruments and Methods in Physics Research Section B: Beam Interactions with Materials and Atoms

2022

Model calibrationLiquid mercury spallation targetEvolutionary neural networks
Multiobjective optimization of nuclear microreactor reactivity control system operation with swarm and evolutionary algorithms
Publication

Multiobjective optimization of nuclear microreactor reactivity control system operation with swarm and evolutionary algorithms

Dean Price, Majdi I. Radaideh, Brendan Kochunas

Nuclear Engineering and Design

2022

Multiobjective optimizationNuclear microreactor reactivitySwarm and evolutionary algorithms
Bayesian inverse uncertainty quantification of the physical model parameters for the spallation neutron source first target station
Publication

Bayesian inverse uncertainty quantification of the physical model parameters for the spallation neutron source first target station

Majdi I. Radaideh, Lianshan Lin, Hao Jiang, et al.

Results in Physics

2022

Bayesian inverse uncertaintyAccelerator physicsSpallation
Large-scale design optimisation of boiling water reactor bundles with neuroevolution
Publication

Large-scale design optimisation of boiling water reactor bundles with neuroevolution

Majdi I. Radaideh, Benoit Forget, Koroush Shirvan

Annals of Nuclear Energy

2021

OptimizationReinforcement learningBoiling water reactor
Rule-based reinforcement learning methodology to inform evolutionary algorithms for constrained optimization of engineering applications
Publication

Rule-based reinforcement learning methodology to inform evolutionary algorithms for constrained optimization of engineering applications

Majdi I. Radaideh, Koroush Shirvan

Knowledge-Based Systems

2021

Reinforcement LearningConstrained optimizationEvolutionary/stochastic algorithms
Physics-informed reinforcement learning optimization of nuclear assembly design
Publication

Physics-informed reinforcement learning optimization of nuclear assembly design

Majdi I. Radaideh, Isaac Wolverton, Joshua Joseph, et al.

Nuclear Engineering and Design

2021

Reinforcement LearningNuclear assembly designStochastic optimization
Multiphysics Modeling and Validation of Spent Fuel Isotopics Using Coupled Neutronics/Thermal-Hydraulics Simulations
Publication

Multiphysics Modeling and Validation of Spent Fuel Isotopics Using Coupled Neutronics/Thermal-Hydraulics Simulations

Dean Price, Majdi I. Radaideh, Travis Mui, et al.

Science and Technology of Nuclear Installations

2020

Multiphysics ModelingSpent Fuel IsotopicsCoupled Neutronics+1
Neural-based time series forecasting of loss of coolant accidents in nuclear power plants
Publication

Neural-based time series forecasting of loss of coolant accidents in nuclear power plants

Majdi I. Radaideh, Connor Pigg, Tomasz Kozlowski, et al.

Expert Systems with Applications

2020

Deep neural networksLong short-term memoryNuclear power plants
Efficient analysis of parametric sensitivity and uncertainty of fuel cell models with application to SOFC
Publication

Efficient analysis of parametric sensitivity and uncertainty of fuel cell models with application to SOFC

Majdi I. Radaideh, Mohammed I. Radaideh, Tomasz Kozlowski

International Journal of Energy Research

2020

Parametric sensitivitySolid oxide fuel cellSobol indices
Design optimization under uncertainty of hybrid fuel cell energy systems for power generation and cooling purposes
Publication

Design optimization under uncertainty of hybrid fuel cell energy systems for power generation and cooling purposes

Majdi I. Radaideh, Mohammed I. Radaideh, Tomasz Kozlowski

International Journal of Hydrogen Energy

2020

Design optimizationHybrid fuel cell energy systemsMonte Carlo
Surrogate modeling of advanced computer simulations using deep Gaussian processes
Publication

Surrogate modeling of advanced computer simulations using deep Gaussian processes

Majdi I. Radaideh, Tomasz Kozlowski

Reliability Engineering & System Safety

2019

Surrogate modelingSimulationGaussian processes
Integrated framework for model assessment and advanced uncertainty quantification of nuclear computer codes under Bayesian statistics
Publication

Integrated framework for model assessment and advanced uncertainty quantification of nuclear computer codes under Bayesian statistics

Majdi I. Radaideh, Katarzyna Borowiec, Tomasz Kozlowski

Reliability Engineering & System Safety

2019

Integrated frameworkNuclear computer codesBayesian statistics
Shapley effect application for variance-based sensitivity analysis of the few-group cross-sections
Publication

Shapley effect application for variance-based sensitivity analysis of the few-group cross-sections

Majdi I. Radaideh, Stuti Surani, Daniel O’Grady, et al.

Annals of Nuclear Energy

2019

Game theoryShapley effectLattice depletion