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Zahra Mohaghegh's directory photo.

Zahra Mohaghegh

Associate Professor

Primary Affiliation

Organizational Intelligence and Computational Social Science


Status Part-time Faculty

Home Department of Nuclear, Plasma and Radiological Engineering



Address 4047 Beckman Institute, 405 North Mathews Avenue

  • Biography

    Zahra Mohaghegh is currently an Assistant Professor in the Department of Nuclear, Plasma, and Radiological Engineering (NPRE) and an affiliate to the Department of Industrial and Enterprise Systems Engineering, the Beckman Institute for Advanced Science and Technology, the School of Information Sciences, Computational Science and Engineering, and the Illinois Informatics Institute at the University of Illinois at Urbana-Champaign.

    Mohaghegh is the Director of the of the Socio-Technical Risk Analysis (SoTeRiA) Research Laboratory ( and Industry Affiliates Program (IAP) ( in the Grainger College of Engineering at UIUC, where she and her research team focus on the advancement of Probabilistic Risk Assessment (PRA) for complex technological systems, pioneering three key areas of scholarly development: (1) spatiotemporal coupling of physical failure mechanisms with human/social performance and generating Integrated PRA (I-PRA), (2) incorporating big data analytics into PRA, and (3) integrating safety risk and financial risk. These three areas have been realized in several of SoTeRiA’s research projects and publications (  

    Mohaghegh is the Principal Investigator of a National Science Foundation (NSF) grant (2015-2020) for big data analytics in PRA, a DOE Nuclear Energy University Program (NEUP) grant (2017-2020) for Enterprise Risk Management (ERM), and a second DOE NEUP grant (2019-2022) for advancing the I-PRA algorithm for the deployment of new technologies. She serves as Co-PI of a $1M project on Fire PRA (2019-2021) with the South Texas Project Nuclear Operating Company (STPNOC) as part of the Department of Energy’s U.S. Industry Opportunities for Advanced Nuclear Technology Development Program. She also serves as a Chief Scientific Investigator and representative of the United States for the International Atomic Energy Agency (IAEA) Coordinated Research Project (2018-2021) for assessing pipe failure rates in advanced water-cooled reactors. Partnering with STPNOC from 2013 to 2017, Mohaghegh and her research team contributed to developing an I-PRA approach for the risk-informed resolution of Generic Safety Issue 191 (GSI-191), providing academic oversight on technical reporting to the Nuclear Regulatory Commission (NRC) and the Advisory Committee on Reactor Safeguards (ACRS). Her work on these projects established her reputation as a leader of industry-focused scientific innovation for risk analysis.

    Mohaghegh is a recipient of the 2016 American Nuclear Society Mary Jane Oestmann Professional Women’s Achievement Award for her innovation in risk analysis, the 2016 Engineering Council Award for Excellence in Advising, the 2015 Dean’s Award for Excellence in Research from the College of Engineering, the George Apostolakis early-career award in risk assessment, and the Zonta International Award for her contribution to modeling large-scale complex systems. She holds a Master’s and a Ph.D. in Reliability Engineering from the University of Maryland and a B.S. in Mechanical Engineering from Sharif University of Technology. 

  • 2019

    • H. Bui, T. Sakurahara, J. Pence, S. Reihani, E. Kee, Z. Mohaghegh, An Algorithm for Enhancing Spatiotemporal Resolution of Probabilistic Risk Assessment to Address Emergent Safety Concerns in Nuclear Power Plants, Reliability Engineering & System Safety, Vol. 185, pp. 405-428, (2019)
    • J. Pence, T. Sakurahara, X. Zhu, Z. Mohaghegh, M. Ertem, C. Ostroff, E. Kee, Data-Theoretic Methodology and Computational Platform to Quantify Organizational Factors in Socio-Technical Risk Analysis, Reliability Engineering & System Safety, Vol. 185, pp. 240-260, (2019)
    • P. Farshadmanesh, T. Sakurahara, S. Reihani, E. Kee, Z. Mohaghegh, SHAKE-RoverD Framework for Nuclear Power Plants: A Streamlined Approach for Seismic Risk Assessment, Nuclear Technology, Vol. 205, Is. 3, pp. 442-463, (2019)
    • T. Sakurahara, G. Schumock, S. Reihani, E. Kee, Z. Mohaghegh, Simulation-Informed Probabilistic Methodology for Common Cause Failure Analysis, Reliability Engineering & System Safety, Vol. 185, pp. 84-99, (2019)


    • • J. Pence, M. Abolhelm, Z. Mohaghegh, S. Reihani, M. Ertem, E. Kee, Methodology to Evaluate the Monetary Benefit of Probabilistic Risk Assessment by Modeling the Net Value of Risk-Informed Applications at Nuclear Power Plants, Reliability Engineering & System Safety, Vol. 175, pp. 171-182, (2018)
    • • T. Sakurahara, Z. Mohaghegh, S. Reihani, E. Kee, M. Brandyberry, S. Rodgers, An integrated methodology for spatio-temporal incorporation of underlying failure mechanisms into fire probabilistic risk assessment of nuclear power plants, Reliability Engineering & System Safety, Vol. 169, pp. 242-257, (2018)
    • J. Pence, I. Miller, T. Sakurahara, J. Whitacre, S. Reihani, E. Kee, Z. Mohaghegh, GIS-Based Integration of Social Vulnerability and Level 3 Probabilistic Risk Assessment to Advance Emergency Preparedness, Planning, and Response for Severe Nuclear Power Plant Accidents, Risk Analysis, (2018)
    • T. Sakurahara, Z. Mohaghegh, S. Reihani, E. Kee, Methodological and Practical Comparison of Integrated Probabilistic Risk Assessment (I-PRA) with the Existing Fire PRA of Nuclear Power Plants, Nuclear Technology, Vol. 204, Is. 3, pp. 354-377, (2018)


    • E. Kee, J. Hasenbein, A. Zolan, P. Grissom, S. Reihani, Z. Mohaghegh, F. Yilmaz, B. Letellier, V. Moiseytseva, R. Vaghetto, RoverD: Use of Test Data in GSI-191 Risk Assessment, Nuclear Technology, Vol. 196, Is. 2, pp. 270-291, (2016)


    • Z. Mohaghegh, A. Mosleh, Incorporating organizational factors into probabilistic risk assessment of complex socio-technical systems: Principles and theoretical foundations, Safety Science, Vol. 47, Is. 8, pp. 1139-1158, (2009)
    • Z. Mohaghegh, A. Mosleh, Measurement techniques for organizational safety causal models: Characterization and suggestions for enhancements, Safety Science, Vol. 47, Is. 10, pp. 1398-1409, (2009)
    • Z. Mohaghegh, R. Kazemi, A. Mosleh, Incorporating organizational factors into Probabilistic Risk Assessment (PRA) of complex socio-technical systems: A hybrid technique formalization, Reliability Engineering & System Safety, Vol. 94, Is. 5, pp. 1000-1018, (2009)