Michael D. Shields

9.4k total citations · 1 hit paper
164 papers, 6.3k citations indexed

About

Michael D. Shields is a scholar working on Statistics, Probability and Uncertainty, Management Information Systems and Accounting. According to data from OpenAlex, Michael D. Shields has authored 164 papers receiving a total of 6.3k indexed citations (citations by other indexed papers that have themselves been cited), including 63 papers in Statistics, Probability and Uncertainty, 38 papers in Management Information Systems and 30 papers in Accounting. Recurrent topics in Michael D. Shields's work include Probabilistic and Robust Engineering Design (61 papers), Accounting and Organizational Management (38 papers) and Auditing, Earnings Management, Governance (29 papers). Michael D. Shields is often cited by papers focused on Probabilistic and Robust Engineering Design (61 papers), Accounting and Organizational Management (38 papers) and Auditing, Earnings Management, Governance (29 papers). Michael D. Shields collaborates with scholars based in United States, United Kingdom and Germany. Michael D. Shields's co-authors include Joan L. Luft, Jiaxin Zhang, Jeffrey F. Shields, Chee W. Chow, Ira Solomon, O. Ray Whittington, George Deodatis, Jacob G. Birnberg, Yutaka Kato and Anne Wu and has published in prestigious journals such as Nature Communications, SHILAP Revista de lepidopterología and Journal of Applied Physics.

In The Last Decade

Michael D. Shields

157 papers receiving 5.7k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

The generalization of Latin hypercube sampling

2015 401 citations Michael D. Shields et al. Reliability Engineering & System Safety profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Michael D. Shields United States	39	2.4k	2.2k	1.1k	1.1k	801	164	6.3k
Malcolm Smith United Kingdom	42	515 0.2×	1.3k 0.6×	105 0.1×	890 0.8×	3.4k 4.2×	242	8.4k
William A. Wallace United States	35	398 0.2×	53 0.0×	1.1k 1.0×	933 0.9×	3.5k 4.4×	266	8.2k
Michael Beer Germany	48	191 0.1×	105 0.0×	5.0k 4.5×	445 0.4×	4.8k 6.0×	485	10.8k
Lin Wang China	43	853 0.4×	100 0.0×	58 0.1×	475 0.4×	165 0.2×	225	7.8k
Michael A. Osborne United Kingdom	25	287 0.1×	143 0.1×	117 0.1×	346 0.3×	85 0.1×	93	7.4k
Han Hong Canada	42	92 0.0×	567 0.3×	901 0.8×	381 0.4×	2.4k 3.0×	297	7.9k
David E. Bell United States	25	360 0.2×	239 0.1×	108 0.1×	363 0.3×	54 0.1×	141	6.4k
Sidney A. Morris Australia	31	98 0.0×	383 0.2×	185 0.2×	986 0.9×	39 0.0×	227	4.5k
James S. Dyer United States	31	412 0.2×	144 0.1×	291 0.3×	566 0.5×	94 0.1×	134	6.0k
Jun Liu China	43	127 0.1×	89 0.0×	395 0.4×	281 0.3×	217 0.3×	455	6.7k

Countries citing papers authored by Michael D. Shields

Since Specialization

Citations

This map shows the geographic impact of Michael D. Shields's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Michael D. Shields with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael D. Shields more than expected).

Fields of papers citing papers by Michael D. Shields

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael D. Shields. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Michael D. Shields. The network helps show where Michael D. Shields may publish in the future.

Co-authorship network of co-authors of Michael D. Shields

This figure shows the co-authorship network connecting the top 25 collaborators of Michael D. Shields. A scholar is included among the top collaborators of Michael D. Shields based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Michael D. Shields. Michael D. Shields is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Markert, Bernd, et al.. (2025). Predicting fracture in disordered network materials using the local intelligent stress threshold indicator. Communications Physics. 8(1). 1 indexed citations

Goswami, Somdatta, et al.. (2025). Synergistic learning with multi-task DeepONet for efficient PDE problem solving. Neural Networks. 184. 107113–107113. 2 indexed citations

Bahmani, Bahador, Somdatta Goswami, Ioannis G. Kevrekidis, & Michael D. Shields. (2025). A resolution independent neural operator. Computer Methods in Applied Mechanics and Engineering. 444. 118113–118113. 4 indexed citations

Shields, Michael D., et al.. (2024). Simulation of non-Gaussian wind field as a 3rd-order stochastic wave. Reliability Engineering & System Safety. 245. 109960–109960. 9 indexed citations

Sharma, Himanshu, et al.. (2024). Physics-informed polynomial chaos expansions. Journal of Computational Physics. 506. 112926–112926. 16 indexed citations

Gaffney, Jim, et al.. (2024). Learning thermodynamically constrained equations of state with uncertainty. SHILAP Revista de lepidopterología. 2(1). 6 indexed citations

Shields, Michael D., et al.. (2024). Physics-constrained polynomial chaos expansion for scientific machine learning and uncertainty quantification. Computer Methods in Applied Mechanics and Engineering. 431. 117314–117314. 11 indexed citations

Deodatis, George & Michael D. Shields. (2024). The Spectral Representation Method: A framework for simulation of stochastic processes, fields, and waves. Reliability Engineering & System Safety. 254. 110522–110522. 10 indexed citations

Graham‐Brady, Lori, et al.. (2024). Bayesian neural networks for predicting uncertainty in full-field material response. Computer Methods in Applied Mechanics and Engineering. 433. 117486–117486. 7 indexed citations

10.

Goswami, Somdatta, et al.. (2023). On the influence of over-parameterization in manifold based surrogates and deep neural operators. Journal of Computational Physics. 479. 112008–112008. 28 indexed citations

11.

Dhulipala, Somayajulu L. N., Yifeng Che, & Michael D. Shields. (2023). Efficient Bayesian inference with latent Hamiltonian neural networks in No-U-Turn Sampling. Journal of Computational Physics. 492. 112425–112425. 3 indexed citations

12.

Shields, Michael D., et al.. (2023). Active learning-based domain adaptive localized polynomial chaos expansion. Mechanical Systems and Signal Processing. 204. 110728–110728. 8 indexed citations

13.

Dhulipala, Somayajulu L. N., Yifeng Che, Wen Jiang, et al.. (2023). General Multifidelity Surrogate Models: Framework and Active-Learning Strategies for Efficient Rare Event Simulation. Journal of Engineering Mechanics. 149(12). 4 indexed citations

14.

Giovanis, Dimitris G., et al.. (2022). A survey of unsupervised learning methods for high-dimensional uncertainty quantification in black-box-type problems. arXiv (Cornell University). 32 indexed citations

15.

Olivier, Audrey, Michael D. Shields, & Lori Graham‐Brady. (2021). Bayesian neural networks for uncertainty quantification in data-driven materials modeling. Computer Methods in Applied Mechanics and Engineering. 386. 114079–114079. 107 indexed citations

16.

Farrell, Anne M., Joan L. Luft, & Michael D. Shields. (2007). Accuracy in Judging the Nonlinear Effects of Cost and Profit Drivers. SSRN Electronic Journal. 1 indexed citations

17.

Luft, Joan L. & Michael D. Shields. (2003). Zimmerman's Contentious Conjectures: Describing the Present and Prescribing the Future of Empirical Management Accounting Research. SSRN Electronic Journal. 5 indexed citations

18.

Solomon, Ira, Michael D. Shields, & O. Ray Whittington. (1999). What Do Industry-Specialist Auditors Know?. SSRN Electronic Journal. 34 indexed citations

19.

Shields, Michael D.. (1997). Research in management accounting by North Americans in the 1990s. Journal of Management Accounting Research. 3–61. 322 indexed citations

20.

Young, S. Mark & Michael D. Shields. (1993). Antecedents and consequences of participative budgeting: Evidence on the effects of asymmetrical. Journal of Management Accounting Research. 265–280. 63 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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