Michael D. Todd

8.0k total citations · 1 hit paper
297 papers, 5.7k citations indexed

About

Michael D. Todd is a scholar working on Civil and Structural Engineering, Mechanics of Materials and Mechanical Engineering. According to data from OpenAlex, Michael D. Todd has authored 297 papers receiving a total of 5.7k indexed citations (citations by other indexed papers that have themselves been cited), including 180 papers in Civil and Structural Engineering, 87 papers in Mechanics of Materials and 75 papers in Mechanical Engineering. Recurrent topics in Michael D. Todd's work include Structural Health Monitoring Techniques (157 papers), Ultrasonics and Acoustic Wave Propagation (78 papers) and Non-Destructive Testing Techniques (42 papers). Michael D. Todd is often cited by papers focused on Structural Health Monitoring Techniques (157 papers), Ultrasonics and Acoustic Wave Propagation (78 papers) and Non-Destructive Testing Techniques (42 papers). Michael D. Todd collaborates with scholars based in United States, China and United Kingdom. Michael D. Todd's co-authors include Eric Flynn, Charles R. Farrar, Gyuhae Park, Lawrence N. Virgin, Zhu Mao, Jonathan M. Nichols, Zhen Hu, Gregg A. Johnson, David Mascareñas and Mark Seaver and has published in prestigious journals such as Proceedings of the National Academy of Sciences, SHILAP Revista de lepidopterología and Analytical Chemistry.

In The Last Decade

Michael D. Todd

282 papers receiving 5.4k 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.

A comprehensive review of digital twin — part 1: modeling and twinning enabling technologies

2022 208 citations Michael D. Todd, Zhen Hu et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Michael D. Todd United States	40	3.2k	1.7k	1.4k	1.2k	749	297	5.7k
Yi‐Qing Ni Hong Kong	53	7.6k 2.4×	1.4k 0.9×	1.7k 1.2×	899 0.7×	1.5k 2.0×	437	10.3k
Eleni Chatzi Switzerland	44	4.5k 1.4×	1.5k 0.9×	1.4k 1.0×	469 0.4×	1.1k 1.5×	333	6.6k
Jean‐Claude Golinval Belgium	34	4.5k 1.4×	1.3k 0.8×	1.4k 1.0×	501 0.4×	1.7k 2.3×	179	6.1k
Patrick Guillaume Belgium	42	4.8k 1.5×	1.5k 0.9×	2.4k 1.8×	672 0.6×	2.2k 3.0×	359	7.6k
Sami F. Masri United States	56	9.0k 2.9×	1.0k 0.6×	2.1k 1.5×	771 0.6×	2.4k 3.1×	267	11.3k
Stefano Mariani Italy	34	1.5k 0.5×	970 0.6×	540 0.4×	670 0.6×	382 0.5×	192	3.1k
Yong Xia Hong Kong	45	6.2k 2.0×	1.9k 1.1×	1.3k 0.9×	341 0.3×	716 1.0×	247	7.3k
Satish Nagarajaiah United States	66	11.5k 3.6×	1.2k 0.7×	1.8k 1.3×	675 0.6×	2.4k 3.2×	281	13.9k
Singiresu S. Rao United States	17	1.1k 0.3×	910 0.5×	905 0.7×	726 0.6×	1.0k 1.3×	57	4.3k
Wei Gao Australia	44	3.9k 1.2×	3.3k 2.0×	1.2k 0.8×	355 0.3×	942 1.3×	291	7.1k

Countries citing papers authored by Michael D. Todd

Since Specialization

Citations

This map shows the geographic impact of Michael D. Todd'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. Todd 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. Todd more than expected).

Fields of papers citing papers by Michael D. Todd

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael D. Todd. 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. Todd. The network helps show where Michael D. Todd may publish in the future.

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

This figure shows the co-authorship network connecting the top 25 collaborators of Michael D. Todd. A scholar is included among the top collaborators of Michael D. Todd 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. Todd. Michael D. Todd 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

Wan, Hua‐Ping, et al.. (2025). An efficient 2D-3D fusion method for bridge damage detection under complex backgrounds with imbalanced training data. Advanced Engineering Informatics. 65. 103373–103373. 5 indexed citations

Todd, Michael D., et al.. (2024). Lagrangian operator inference enhanced with structure-preserving machine learning for nonintrusive model reduction of mechanical systems. Computer Methods in Applied Mechanics and Engineering. 423. 116865–116865. 7 indexed citations

Zeng, Jice, et al.. (2024). Bayesian Model Updating of Multiscale Simulations Informing Corrosion Prognostics Using Conditional Invertible Neural Networks. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems Part B Mechanical Engineering. 11(1). 2 indexed citations

Quinn, D. Dane, et al.. (2024). A structure-preserving machine learning framework for accurate prediction of structural dynamics for systems with isolated nonlinearities. Mechanical Systems and Signal Processing. 213. 111340–111340. 8 indexed citations

Zeng, Jice, Michael D. Todd, Zhao Zhao, & Zhen Hu. (2024). Model uncertainty quantification of a degradation model of miter gates using normalizing flow-based likelihood-free inference. Structural Health Monitoring. 24(4). 2064–2090. 1 indexed citations

Hu, Zhen, et al.. (2024). Pitting corrosion diagnostics and prognostics for miter gates using multiscale simulation and image inspection data. Structural Health Monitoring. 24(4). 2008–2030. 2 indexed citations

Zhao, Ying, et al.. (2024). Physics-enhanced machine learning models for streamflow discharge forecasting. Journal of Hydroinformatics. 26(10). 2506–2537. 3 indexed citations

Hu, Zhen, et al.. (2024). A value-of-information-based optimal sensor placement design framework for cost-effective structural health monitoring (with application to miter gate monitoring). Structural Health Monitoring. 24(4). 2091–2124.

Chatzi, Eleni, Dániel Straub, Nikolaos Dervilis, et al.. (2024). Monitoring-supported value generation for managing structures and infrastructure systems. SHILAP Revista de lepidopterología. 5. 2 indexed citations

10.

Zeng, Jice, Michael D. Todd, & Zhen Hu. (2023). A recursive inference method based on invertible neural network for multi-level model updating using video monitoring data. Mechanical Systems and Signal Processing. 203. 110736–110736. 11 indexed citations

11.

Hu, Zhen, et al.. (2023). Physics-based corrosion reliability analysis of miter gates using multi-scale simulations and adaptive surrogate modeling. Mechanical Systems and Signal Processing. 200. 110619–110619. 4 indexed citations

12.

Kim, Sunny, Michael D. Todd, Linda Larkey, et al.. (2022). Effects of a Digital Storytelling Intervention on Psychosocial Well-Being for Patients and Caregivers Undergoing Hematopoietic Cell Transplantation. Transplantation and Cellular Therapy. 28(3). S49–S49. 1 indexed citations

13.

Todd, Michael D., et al.. (2021). Active scour monitoring using ultrasonic time domain reflectometry of buried slender sensors. Smart Materials and Structures. 31(1). 15045–15045. 3 indexed citations

14.

Farinholt, Kevin, et al.. (2013). Wireless Active Sensing Platform for Structural Infrastructure Monitoring. Structural Health Monitoring. 2 indexed citations

15.

Todd, Michael D., et al.. (2013). Effect of Applied Load on Guided Wave Monitoring of a Composite Bolted Joint. Structural Health Monitoring. 1 indexed citations

16.

Farrar, Charles R., Eric Flynn, & Michael D. Todd. (2010). A Bayesian experimental design approach to structural health monitoring. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 2 indexed citations

17.

Salamone, Salvatore, et al.. (2009). Health Monitoring Approach for Adhesively Bonded Joints. Materials Evaluation. 67(7). 828–836. 6 indexed citations

18.

Vohra, S. T., et al.. (2000). Distributed Strain Monitoring with Arrays of Fiber Bragg Grating Sensors on an In-Construction Steel Box-Girder Bridge. IEICE Transactions on Electronics. 454–461. 3 indexed citations

19.

Todd, Michael D., et al.. (1999). Bridge monitoring using a 64-channel fiber bragg grating system. 3727. 1719–1725. 2 indexed citations

20.

Todd, Michael D., et al.. (1999). Performance of Elastic Beam Fiber Bragg Grating Accelerometers. Optical Fiber Sensors. 3746. 545–548. 1 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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