M. J. Schulz

1.4k citations
39 papers · 1.1k · h-index 17

Impact in

Papers in

M. J. Schulz

38 papers receiving 993 citations

Peers

M. J. Schulz
Comparison fields: 5 of 71
  • Civil and Structural Engineering 631
  • Mechanics of Materials 461
  • Mechanical Engineering 287
  • Biomedical Engineering 328
  • Statistics, Probability and Uncertainty 49
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Kevin Farinholt United States
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Thomas Gmür Switzerland
Jeong‐Beom Ihn United States
Hu Sun China
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Emmanuel Ayorinde United States
Ajay Raghavan United States
J.L. Curiel-Sosa United Kingdom
Asif Khan South Korea
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Citations per field
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Citations per year

Countries citing papers authored by M. J. Schulz

Since Specialization
Citations

This map shows the geographic impact of M. J. Schulz'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 M. J. Schulz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites M. J. Schulz more than expected).

Fields of papers citing papers by M. J. Schulz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by M. J. Schulz. 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 M. J. Schulz. The network helps show where M. J. Schulz may publish in the future.

Co-authors

The 25 scholars most cited alongside M. J. Schulz, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with M. J. Schulz Line = papers co-authored together M. J. Schulz links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 39 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2008194
2 1999108
3 1998105
4 199881
5 200869
6 199968
7 200254
8 200351
9 200338
10 200725
11 200324
12 200123
13 200120
14
Detecting Structural Damage Using Transmittance Functions
199719
15 199419
16 200118
17 200217
18
Structural Health Monitoring Using Frequency Response Functions and Sparse Measurements
199816
19 200516
20 200513

About M. J. Schulz

M. J. Schulz is a scholar working on Civil and Structural Engineering, Mechanics of Materials, Biomedical Engineering, Mechanical Engineering and Electrical and Electronic Engineering, having authored 39 papers that have together received 1.1k indexed citations. Recurring topics across this work include Structural Health Monitoring Techniques (22 papers), Ultrasonics and Acoustic Wave Propagation (15 papers), Carbon Nanotubes in Composites (4 papers), Aeroelasticity and Vibration Control (4 papers), Optical measurement and interference techniques (4 papers), Smart Materials for Construction (4 papers), Acoustic Wave Resonator Technologies (3 papers) and Vibration Control and Rheological Fluids (3 papers). The work is most often cited by research in Civil and Structural Engineering (631 citations), Mechanics of Materials (461 citations), Mechanical Engineering (287 citations), Biomedical Engineering (328 citations) and Statistics, Probability and Uncertainty (49 citations). M. J. Schulz has collaborated with scholars based in United States, Germany and South Korea. Frequent co-authors include P. Frank Pai, Ahmad S. Naser, Daniel J. Inman, M. Sundaresan, Frederick Ferguson, Soo‐Hyun Lee, Chunyan Li, Peiming Wu, Chong H. Ahn and Anindya Ghoshal. Their work appears in journals such as Journal of Sound and Vibration, Shock and Vibration, Journal of Intelligent Material Systems and Structures, Mechanical Systems and Signal Processing and Smart Materials and Structures.

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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