Work Experience
- Reliability Engineer | NIST, Gaithersburg, MD (Feb 2024 – Present)
Developed Bayesian network models for safety-related systems in NIST’s research reactor. Analyzed degradation and assisted with relicensing efforts for long-term operations.
- Mechanical Engineer | NIST, Gaithersburg, MD (Aug 2019 – Aug 2023)
Performed CFD analysis and developed CAD models for the design of a new neutron source.
Research Experience
- Graduate Research Assistant | University of Maryland, College Park, MD
Conducted pioneering research in external flood PRAs using Monte Carlo augmented Bayesian networks. Investigated nuclear power plant risks and contributed to the U.S. NRC’s efforts to assess system vulnerabilities during external floods.
- Associate Researcher | NIST, Gaithersburg, MD
Conducted neutron energy spectrum measurements, proving the viability of Cf-250 as a calibration source for radiation instrumentation.
Skills and Certifications
- CAD: Solidworks, Autodesk Inventor
- Programming: MATLAB, Python, IGOR
- Accident Analysis: MCNP, RELAP5, TRACE, SNAP
- Probabilistic Tools: SAPHIRE, GeNIE, Minitab
- Certifications: 10 CFR 50.59 Training, Procedure Professionals Association (PPA)
Research Interests
Ms. Joy’s research interests focus on probabilistic risk assessments (PRA), Bayesian networks, nuclear reactor safety, and external flood risk assessments. She is passionate about enhancing the reliability and safety of critical infrastructure through advanced analytical models.
Publications
A Monte Carlo augmented Bayesian network approach for external flood PRAs
- Authors: Shen, J., Bensi, M., Modarres, M.
- Year: 2025
A Hybrid, Bayesian Network-Based PRA Methodology for External Flood Probabilistic Risk Assessments at Nuclear Power Plants
- Authors: Shen, J., Frantzis, C., Marandi, S., Bensi, M., Modarres, M.
- Year: 2023
Synthesis of Insights Regarding Current PRA Technologies for Risk-Informed Decision Making
- Authors: Shen, J., Marandi, S., Bensi, M., Modarres, M.
- Year: 2023