Majdi Radaideh (RAD)

Massachusetts Institute of Technology

Postdoctoral studies (Nov. 2019 – Aug. 2021)

Focus: Nuclear reactor design with deep reinforcement learning

University of Illinois at Urbana-Champaign

PhD Nuclear Engineering (Aug. 2016 – Aug. 2019)

Dissertation: A Novel Framework for Data-driven Modeling, Uncertainty Quantification, and Deep Learning of Nuclear Reactor Simulations

Minor 1: Computational Science and Engineering (May 2019).

Minor 2: Applied Statistics (May 2019).

University of Illinois at Urbana-Champaign

M.Sc. Nuclear Engineering (Aug. 2015 – Aug. 2016)

Thesis: Analysis of Reverse Flow Restriction Device to Prevent Fuel Dryout during Loss of Coolant and Instability Accidents of Boiling Water Reactors

Jordan University of Science and Technology

B.Sc. Nuclear Engineering (Aug. 2009 – Dec. 2013)

Graduated 1^st of the class and with highest honor.

AIMS lab focuses on the intersection between reactor design, nuclear multiphysics modeling and simulation, advanced computational methods, and machine learning algorithms to drive advanced reactor research and improve the sustainability of the current reactor fleet. AIMS focuses on three broad thrust areas:

• Multiphysics Reactor Design: We study high-fidelity multiphysics phenomena and safety aspects of light water, advanced, small modular, and microreactors. The topics of interest are: Reactor design, multiphysics coupling, core, and design optimization, nuclear data assessment, spent fuel analysis, accident & safety analysis, and experimental validation.
• Advanced Computing: We develop and apply advanced computing algorithms for all fields of nuclear engineering (fission, plasma, materials, radiology). We focus on both algorithms research and real-world applications in the field. The topics of interest are: Physics-informed machine learning, deep learning, uncertainty quantification, surrogate modeling, evolutionary optimization, and Bayesian inversion.
• Autonomous control: We develop and apply physics-based and data-driven modeling techniques on continuous data streams for control in digital electronics to improve system efficiency and reduce operation and maintenance costs. The topics of interest are: Digital twins, anomaly detection, fault prognostics, reinforcement learning, model predictive control, and component health monitoring.

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ANS

• Reactor Physics Division
• Mathematics & Computation Division

NEA

ASME

• Nuclear Engineering Division
• Computers & Information in Engineering Division
• Dynamic Systems & Control Division

IEEE

• IEEE-Computational Intelligence Society
• IEEE-Robotics and Automation Society
• IEEE-Control Systems Society

Jan. 2023 – Present: Assistant Professor, Nuclear Engineering & Radiological Sciences, University of Michigan, Ann Arbor, MI.

Nov. 2021 – Dec. 2022: Machine Learning Engineer for Analysis & Control of Complex Systems, Spallation Neutron Source, Oak Ridge National Laboratory, Oak Ridge, TN.

Aug. 2021 – Nov. 2021: Research Scientist, Department of Nuclear Science and Engineering, Massachusetts Institute of Technology, Cambridge, MA.

Nov. 2019 – Aug. 2021: Postdoctoral Research Associate, Department of Nuclear Science and Engineering, Massachusetts Institute of Technology, Cambridge, MA.

June 2021 – Aug. 2021: Lead instructor, S21S: MIT-INL AI-ML Summer 2021 Symposium, Idaho National Laboratory, Idaho Falls, Idaho.

June 2017 – Aug. 2017: Research Intern, Reactor and Nuclear Systems Divison, Oak Ridge National Laboratory, Oak Ridge, TN.

• 2023: DOE-NE Distinguished Early Career Program Award
• 2021: Postdoctoral Outstanding Service Award, Nuclear Science and Engineering, MIT, Cambridge, MA.
• 2019: ANS National Mark Mills Award for the best PhD thesis work in nuclear engineering, La Grange Park, IL.
• 2018: University of Illinois Graduate College Fellowship, Nuclear, Plasma, and Radiological Engineering, University of Illinois Urbana-Champaign, Urbana, IL.
• 2018: Best Paper Award in the Best Estimate Plus Uncertainty Conference (BEPU-2018), Lucca, Italy.
• 2018: “Sampling-Based Uncertainty Quantification of the Six-group Kinetic Parameters” was selected among the best papers in the Physics of Reactors (PHYSOR-2018) conference, Cancun, Mexico. The paper was published in the conference special issue in Annals of Nuclear Energy.
• 2018: Bruce W. Spencer Graduate Award for outstanding research work in nuclear reactor safety, Department of Nuclear, Plasma, and Radiological Engineering, University of Illinois at Urbana-Champaign, Urbana, IL.
• 2017: Best Poster Award in the NESLS summer internship program, Oak Ridge National Laboratory, Oak Ridge, TN.
• 2016: ANS Alpha Nu Sigma National Honor Society (inducted 2016).
• 2014: Excellence Plaque in Engineering for the distinct 2014’s engineering graduates in the country of Jordan. REXROTH Bosch Group and PRO Train Academy, Amman, Jordan.
• 2012: National Academic Excellence Prize after being nominated by the JUST university to be among the top 10 undergraduate students around the country of Jordan. Arab Banking Corporation, Amman, Jordan.