Michael D. Shields

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Dimitris G GiovanisAssistant Research Professor, John Hopkins University, Civil EngineeringVerified email at jhu.edu
Jiaxin ZhangIntuit AI Research; Oak Ridge National Lab; Johns Hopkins UniversityVerified email at intuit.com
Katiana KontolatiPhD, Johns Hopkins UniversityVerified email at jhu.edu
George DeodatisProfessor of Civil Engineering and Engineering Mechanics, Columbia UniversityVerified email at civil.columbia.edu
Lohit VandanapuPhD Candidate, Johns Hopkins UniversityVerified email at jhu.edu
Somdatta GoswamiAssistant Professor, Civil and Systems Engineering, Johns Hopkins UniversityVerified email at jh.edu
Somayajulu L. N. DhulipalaComputational Scientist, Idaho National LabVerified email at inl.gov
Sundar VelkurSr Data Scientist, Topgolf Callaway BrandsVerified email at callawaygolf.com
Lori Graham-BradyJohns Hopkins UniversityVerified email at jhu.edu
George Em KarniadakisThe Charles Pitts Robinson and John Palmer Barstow Professor of Applied Mathematics and EngineeringVerified email at brown.edu
Michael L. FalkProfessor of Materials Science and Engineering, Johns Hopkins UniversityVerified email at jhu.edu
Raymond DaddazioThornton TomasettiVerified email at thorntontomasetti.com
Kirubel TeferraU.S. Naval Research LaboratoryVerified email at nrl.navy.mil
Promit ChakrobortyPh.D. Student, Dept of Civil and Systems Engg., Johns Hopkins UniversityVerified email at jhu.edu
Dimitrios LoukrezisResearch scientist, Siemens AG | Research group leader, TU DarmstadtVerified email at temf.tu-darmstadt.de
Pawel WoelkeThornton Tomasetti / Columbia UniversityVerified email at thorntontomasetti.com
Hwanpyo KimJohns Hopkins UniversityVerified email at jhu.edu
Paolo BocchiniProfessor and Director of the Center for Catastrophe Modeling and Resilience, Lehigh UniversityVerified email at lehigh.edu
Audrey OlivierAssistant Professor of Civil and Environmental Engineering, USCVerified email at usc.edu
Benjamin SpencerIdaho National LaboratoryVerified email at inl.gov

Michael D. Shields

Johns Hopkins University

Verified email at jhu.edu - Homepage

uncertainty quantification computational mechanics stochastic processes


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
The generalization of Latin hypercube sampling MD Shields, J Zhang Reliability Engineering & System Safety 148, 96-108, 2016	449	2016
A simple and efficient methodology to approximate a general non-Gaussian stationary stochastic process by a translation process MD Shields, G Deodatis, P Bocchini Probabilistic Engineering Mechanics 26 (4), 511-519, 2011	188	2011
Refined stratified sampling for efficient Monte Carlo based uncertainty quantification MD Shields, K Teferra, A Hapij, RP Daddazio Reliability Engineering and System Safety 142, 310-325, 2015	140	2015
Bayesian neural networks for uncertainty quantification in data-driven materials modeling A Olivier, MD Shields, L Graham-Brady Computer Methods in Applied Mechanics and Engineering 386, 114079, 2021	100	2021
On the quantification and efficient propagation of imprecise probabilities resulting from small datasets J Zhang, MD Shields Mechanical Systems and Signal Processing 98, 465-483, 2018	99	2018
Modeling strongly non-Gaussian non-stationary stochastic processes using the Iterative Translation Approximation Method and Karhunen–Loève expansion H Kim, MD Shields Computers & Structures 161, 31-42, 2015	92	2015
A simple and efficient methodology to approximate a general non-Gaussian stationary stochastic vector process by a translation process with applications in wind velocity simulation MD Shields, G Deodatis Probabilistic Engineering Mechanics 31, 19-29, 2013	87	2013
UQpy: A general purpose Python package and development environment for uncertainty quantification A Olivier, D Giovanis, BS Aakash, M Chauhan, L Vandanapu, MD Shields Journal of Computational Science 47, 101204, 2020	76	2020
Deep transfer operator learning for partial differential equations under conditional shift S Goswami, K Kontolati, MD Shields, GE Karniadakis Nature Machine Intelligence 4 (12), 1155-1164, 2022	75	2022
Estimation of evolutionary spectra for simulation of non-stationary and non-Gaussian stochastic processes MD Shields, G Deodatis Computers & Structures 126, 149-163, 2013	68	2013
Cohesive zone modeling and calibration for mode I tearing of large ductile plates PB Woelke, MD Shields, JW Hutchinson Engineering Fracture Mechanics 147, 293-305, 2015	64	2015
Simulations of ductile fracture in an idealized ship grounding scenario using phenomenological damage and cohesive zone models PB Woelke, MD Shields, NN Abboud, JW Hutchinson Computational Materials Science 80, 79-95, 2013	58	2013
Surrogate-enhanced stochastic search algorithms to identify implicitly defined functions for reliability analysis VS Sundar, MD Shields Structural Safety 62, 1-11, 2016	53	2016
Coarse graining atomistic simulations of plastically deforming amorphous solids AR Hinkle, CH Rycroft, MD Shields, ML Falk Physical Review E 95 (5), 053001, 2017	51	2017
Topology optimization for linear stationary stochastic dynamics: Applications to frame structures M Zhu, Y Yang, JK Guest, MD Shields Structural Safety 67, 116-131, 2017	49	2017
Variance-based adaptive sequential sampling for Polynomial Chaos Expansion L Novák, M Vořechovský, V Sadílek, MD Shields Computer Methods in Applied Mechanics and Engineering 386, 114105, 2021	48	2021
Data-driven surrogates for high dimensional models using Gaussian process regression on the Grassmann manifold DG Giovanis, MD Shields Computer Methods in Applied Mechanics and Engineering 370, 113269, 2020	47	2020
Simulation of spatially correlated nonstationary response spectrum–compatible ground motion time histories MD Shields Journal of Engineering Mechanics 141 (6), 04014161, 2015	44	2015
On the influence of over-parameterization in manifold based surrogates and deep neural operators K Kontolati, S Goswami, MD Shields, GE Karniadakis Journal of Computational Physics 479, 112008, 2023	42	2023
Reliability analysis using adaptive kriging surrogates with multimodel inference VS Sundar, MD Shields ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A …, 2019	42	2019

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