Director, Center for Risk and Reliability
Maryland Energy Innovation Institute
Center for Risk and Reliability
- Ph.D., Massachusetts Institute of Technology, 1980
Dr. Modarres is the Nicole Y. Kim Eminent Professor of Engineering and Director, Center for Risk and Reliability at the University of Maryland, College Park. He is an expert in reliability engineering, probabilistic risk assessment, physics of failure, and fracture mechanics. His interests in risk, reliability, structural integrity and prognosis, and health management include both experimental and probabilistic model development efforts. He has over 450 papers in archival journals and proceedings of conferences including multiple textbooks and book chapters in various areas of risk and reliability engineering. He is a recipient of multiple awards. Dr. Modarres received his BS in Mechanical Engineering from Tehran Polytechnic, MS in Mechanical Engineering from MIT, and MS and Ph.D. in Nuclear Engineering also from MIT.
SELECTED HONORS AND AWARDS
- Nicole Y. Kim Eminent Professorship in Engineering
- Minta Martin Professorship in A.J. Clark School of Engineering
- University of Maryland Distinguished Scholar-Teacher
- 2019 Tommy Thompson Award for outstanding lifetime contributions to nuclear safety, American Nuclear Society
- Fellow, American Nuclear Society
- 1996 Maryland Inventor of the Year Award (in Information Sciences)
- FDA Commissioner Special Citation for Contributions to Risk Assessment Methods, 2004
- 2008 International Research Leadership Award conferred by the Society for Reliability Engineering, Quality and Operations Management
Probabilistic risk assessment, Uncertainty analysis, Probabilistic Physics of Failure, Fracture Mechanics, Prognosis and Health Management
Recent Books and Journal Papers
- Probabilistic Risk Assessment, Wiley Encyclopedia of Electrical and Electronics Engineering, John Wiley & Sons, 2018.Reliability Engineering and Risk Analysis: A Practical Guide, M. Modarres, M. Kaminskiy, and V. Krivtsov, CRC Press, New York, N.Y., 1st Ed. (1999), 2nd Ed. (2010), 3rd Ed. (2017).
- Probabilistic Physics of Failure, in Advances in Performability Engineering, Prof. Krishna Misra (Ed.), (2021), ISBN 978-3-030-55732-4.
- Probabilistic Risk Assessment, Encyclopedia of Nuclear Energy, Professor Ehud Greenspan & Dr. Joy Rempe (Eds.), Elsevier, 2021, ISBN: 9780128197257.
- Probabilistic Risk Assessment, Wiley Encyclopedia of Electrical and Electronics Engineering, John Wiley & Sons, 2018.
Big Machinery Data Preprocessing Methodology for Data-Driven Models in Prognostics and Health Management, S. Cofre-Martel, E. Droguett, M. Modarres, Sensors, October 2021, 21(20), 6841; https://doi.org/10.3390/s21206841
A Bayesian Network Approach for Modeling Dependent Seismic Failures in a Nuclear Power Plant Probabilistic Risk Assessment, J. DeJesus Segarra, M. Bensi, M. Modarres, Submitted Reliability Engineering and System Safety J., 213 (2021) 107678, https://doi.org/10.1016/j.ress.2021.107678
Multi-Unit Nuclear Power Plant Probabilistic Risk Assessment: A Comprehensive Survey, T. Zhou, M. Modarres, E. López Droguett. Submitted for publication to Reliability Engineering and System Safety J. Reliability Engineering and System Safety 213 (2021) 107782, https://doi.org/10.1016/j.ress.2021.107782
Acoustic emission signal clustering in CFRP laminates using a new feature set based on waveform analysis and information entropy analysis, S. F. Karimian, M. Modarres, Composite Structures J., Vol. 268, July 2021, 113987, https://doi.org/10.1016/j.compstruct.2021.113987
Remaining Useful Life Estimation Through Deep Learning Partial Differential Equation Models: A Framework for Degradation Dynamics Interpretation Using Latent Variables, S. Cofre, E. López Droguett, M. Modarres, Shock and Vibration. 2021, 9937846, https://doi.org/10.1155/2021/9937846
Understanding and Effectively Managing Conservatisms in Safety Analysis, M. Modarres, S. Krahn, J. O’Brien, Nuclear Technology J., 2020, https://doi.org/10.1080/00295450.2020.1805258
Layout Optimization of Multi-type Sensors and Human Inspection Tools with Probabilistic Detection of Localized Damages for Pipelines, A. Aria, S. Azarm, and M. Modarres, IEEE Access J., Vol. 9, 10.1109/ACCESS.2020.2992671.
Extension of Probabilistic Seismic Hazard Analysis to Account for Spatial Variability of Ground Motions at a Multi-Unit Nuclear Power Plant Site, J. DeJesus-Segarra, M. Bensi, M. Modarres, and T. Weaver, Structural Safety J., Vol. 85, 101985, https://doi.org/10.1016/j.strusafe.2020.101958.
A Deep Adversarial Approach Based on Multi-sensor Fusion for Semi-supervised Remaining Useful Life Prognostics, D. Verstraete, E. Droguett, M. Modarres, Sensors, 20, 176 (2020), https://doi:10.3390/s20010176.
A Common Cause Failure Model for Components Under Age-Related Degradation, T. Zhou, E. Droguett, M. Modarres, Reliability Engineering and System Safety J., Vol.195 (2020), https://doi.org/10.1016/j.ress.2019.106699.
A New Method for Detecting Fatigue Crack Initiation in Aluminum Alloy Using Acoustic Emission Waveform Information Entropy, S. F. Karimian, H. A. Bruck, and M. Modarres, Engineering Fracture Mechanics, Vol. 223 (2020) https://doi.org/10.1016/j.engfracmech.2019.106771.
Thermodynamic Entropy to Detect Fatigue Crack Initiation Using Digital Image Correlation, and Effect of Overload Spectrums, F. Karimian, H. Bruck, M. Modarres, International Journal of Fatigue, 129 (2019). https://doi.org/10.1016/j.ijfatigue.2019.105256.
Estimation of Damage Size and Remaining Useful Life in Degraded Structures through Deep-Learning Based Multi-Source Data Fusion, A. Aria, E. Droguett, S. Azarm, and M. Modarres, Structural Health Monitoring J., (2019). https://doi.org/10.1177/1475921719890616
Modeling Uncertainty in Reliability Growth Planning for Discrete-Use Systems, P. Nation and M. Modarres, Australian Journal of Multidisciplinary Engineering, Vol. 15, No.1, 2019. https://doi.org/10.1080/14488388.2019.1661808.
Measures of Entropy to Characterize Fatigue Damage in Metallic Materials, H. Yun and M. Modarres, Entropy J., 21, 804. DOI: https://doi.org/10.3390/e21080804.
Deep Semi-Supervised Generative Adversarial Fault Diagnostics of Rolling Element Bearings, D. Verstraete, E. Droguett, A. Ferrada, V. Meruane, M. Modarres, Structural Health Monitoring J., pp.1–22 (2019). DOI: https://doi.org/10.1177/1475921719850576.
Multi-Unit Risk Aggregation with Consideration of Uncertainty and Bias in Risk Metrics, T. Zhou, M. Modarres, E. Droguett, Reliability Engineering and System Safety J., Volume 188, Pages 473-482,(2019), https://doi.org/10.1016/j.ress.2019.04.001.
- American Nuclear Society