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Michael Shields is an associate professor of civil and systems engineering. His research focuses on uncertainty quantification for wide-ranging problems in computational mechanics and computational materials science.
His group, the Shields Uncertainty Research Group (SURG), conducts methodological research in uncertainty quantification, machine learning, and stochastic methods to better understand the effects of uncertainties and random variations on the performance of materials and structures. This research can be applied to boost structural resilience during extreme events such as fires, earthquakes, high winds, blasts, and impacts by enabling more accurate and informative structural and material modeling. Shields’ work primarily focuses on problems where computational efficiency is critical and the behavior of the system is highly unpredictable, such as in civil structures, aircraft, ships, automobiles, and spacecraft.
SURG develops the open-source UQpy (Uncertainty Quantification with Python) software package for modeling uncertainty in the simulation of physical and mathematical systems. This novel tool was designed to aid computational analyses using numerical, statistically, and machine learning approaches, such as polynomial chaos expansions, Gaussian process regression and Monte Carlo sampling.
Shields research has received funding from the National Science Foundation (NSF), Office of Naval Research (ONR), Army Research Laboratory, Idaho National Laboratory, Sandia National Laboratory, Defense Threat Reduction Agency, and Hopkins Extreme Materials Institute (HEMI). He is the recipient of the Department of Energy Early Career Award, NSF CAREER Award, ONR Young Investigator Award, the Johns Hopkins University Catalyst Award, an ONR Summer Faculty Research Fellowship, and an NSF/ASEE Corporate Research Postdoctoral Fellowship. Since 2011, he has had more than 45 papers published in academic journals.
Shields is an active member of several professional organizations, including the American Society of Civil Engineers, American Society of Mechanical Engineers, U.S. Association for Computational Mechanics, and Society of Industrial and Applied Mathematics, International Civil Engineering Risk and Reliability Association, International Association on Structural Safety and Reliability, and the Materials Research Society. He has served as a peer reviewer for at least 27 academic journals.
In 2006, Shields received dual bachelor’s degrees in Physics and Civil Engineering from Loyola University Chicago and Columbia University, respectively. He completed his PhD in Civil Engineering and Engineering Mechanics at Columbia University in 2010. Prior to joining Johns Hopkins in 2013, he was a research engineer in the Applied Science and Investigations group at Weidlinger Associates, Inc. (now Weidlinger Applied Science at Thornton Tomasetti). He holds a secondary appointment in the Department of Materials Science and Engineering.
His group, the Shields Uncertainty Research Group (SURG), conducts methodological research in uncertainty quantification, machine learning, and stochastic methods to better understand the effects of uncertainties and random variations on the performance of materials and structures. This research can be applied to boost structural resilience during extreme events such as fires, earthquakes, high winds, blasts, and impacts by enabling more accurate and informative structural and material modeling. Shields’ work primarily focuses on problems where computational efficiency is critical and the behavior of the system is highly unpredictable, such as in civil structures, aircraft, ships, automobiles, and spacecraft.
SURG develops the open-source UQpy (Uncertainty Quantification with Python) software package for modeling uncertainty in the simulation of physical and mathematical systems. This novel tool was designed to aid computational analyses using numerical, statistically, and machine learning approaches, such as polynomial chaos expansions, Gaussian process regression and Monte Carlo sampling.
Shields research has received funding from the National Science Foundation (NSF), Office of Naval Research (ONR), Army Research Laboratory, Idaho National Laboratory, Sandia National Laboratory, Defense Threat Reduction Agency, and Hopkins Extreme Materials Institute (HEMI). He is the recipient of the Department of Energy Early Career Award, NSF CAREER Award, ONR Young Investigator Award, the Johns Hopkins University Catalyst Award, an ONR Summer Faculty Research Fellowship, and an NSF/ASEE Corporate Research Postdoctoral Fellowship. Since 2011, he has had more than 45 papers published in academic journals.
Shields is an active member of several professional organizations, including the American Society of Civil Engineers, American Society of Mechanical Engineers, U.S. Association for Computational Mechanics, and Society of Industrial and Applied Mathematics, International Civil Engineering Risk and Reliability Association, International Association on Structural Safety and Reliability, and the Materials Research Society. He has served as a peer reviewer for at least 27 academic journals.
In 2006, Shields received dual bachelor’s degrees in Physics and Civil Engineering from Loyola University Chicago and Columbia University, respectively. He completed his PhD in Civil Engineering and Engineering Mechanics at Columbia University in 2010. Prior to joining Johns Hopkins in 2013, he was a research engineer in the Applied Science and Investigations group at Weidlinger Associates, Inc. (now Weidlinger Applied Science at Thornton Tomasetti). He holds a secondary appointment in the Department of Materials Science and Engineering.
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Reliability Engineering & System Safetypp.109960, (2024)
Mohit S. Chauhan,Mariel Ojeda-Tuz,Ryan A. Catarelli,Kurtis R. Gurley, Dimitrios Tsapetis,Michael D. Shields
RELIABILITY ENGINEERING & SYSTEM SAFETY (2024): 109945
Journal of Computational Physics (2024): 112926
CoRR (2024)
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Dimitrios Tsapetis,Michael D. Shields,Dimitris G. Giovanis,Audrey Olivier,Lukas Novak,Promit Chakroborty, Himanshu Sharma,Mohit Chauhan,Katiana Kontolati,Lohit Vandanapu,Dimitrios Loukrezis, Michael Gardner
SOFTWAREX (2023): 101561-101561
Proceedings in Applied Mathematics & Mechanics (2023)
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