Erik Glatt

1.6k total citations · 2 hit papers
33 papers, 1.3k citations indexed

About

Erik Glatt is a scholar working on Computational Mechanics, Computer Networks and Communications and Statistical and Nonlinear Physics. According to data from OpenAlex, Erik Glatt has authored 33 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Computational Mechanics, 9 papers in Computer Networks and Communications and 9 papers in Statistical and Nonlinear Physics. Recurrent topics in Erik Glatt's work include stochastic dynamics and bifurcation (9 papers), Nonlinear Dynamics and Pattern Formation (9 papers) and Neural dynamics and brain function (7 papers). Erik Glatt is often cited by papers focused on stochastic dynamics and bifurcation (9 papers), Nonlinear Dynamics and Pattern Formation (9 papers) and Neural dynamics and brain function (7 papers). Erik Glatt collaborates with scholars based in Germany, United States and Japan. Erik Glatt's co-authors include Andreas Wiegmann, Heiko Andrä, Matthias Kabel, Claudio Madonna, Youngseuk Keehm, Tapan Mukerji, Erik H. Saenger, Ratnanabha Sain, Jack Dvorkin and Nicolas Combaret and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and International Journal of Solids and Structures.

In The Last Decade

Erik Glatt

30 papers receiving 1.3k citations

Hit Papers

Digital rock physics benchmarks—Part I: Imaging and segme... 2012 2026 2016 2021 2012 2012 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Erik Glatt Germany 12 724 544 413 302 189 33 1.3k
James W. Jennings United States 21 767 1.1× 489 0.9× 848 2.1× 173 0.6× 39 0.2× 86 1.6k
B. Biswal India 14 267 0.4× 256 0.5× 129 0.3× 48 0.2× 61 0.3× 24 532
Sadegh Karimpouli Iran 19 553 0.8× 497 0.9× 457 1.1× 339 1.1× 48 0.3× 37 1.2k
Matthias Kabel Germany 18 731 1.0× 1.4k 2.6× 659 1.6× 326 1.1× 282 1.5× 37 2.2k
Dong Liu China 26 96 0.1× 599 1.1× 532 1.3× 336 1.1× 98 0.5× 94 1.7k
Nanzhe Wang China 16 329 0.5× 62 0.1× 267 0.6× 141 0.5× 108 0.6× 21 796
Ning Guo China 24 141 0.2× 750 1.4× 182 0.4× 67 0.2× 730 3.9× 80 2.3k
Kundan Kumar Norway 20 184 0.3× 330 0.6× 140 0.3× 50 0.2× 491 2.6× 60 1.3k
Erlend Magnus Viggen Norway 9 242 0.3× 80 0.1× 194 0.5× 43 0.1× 1.5k 7.8× 28 1.9k
Thomas Schwager Germany 18 509 0.7× 306 0.6× 243 0.6× 63 0.2× 1.4k 7.4× 27 1.9k

Countries citing papers authored by Erik Glatt

Since Specialization
Citations

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

Fields of papers citing papers by Erik Glatt

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Erik Glatt. 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 Erik Glatt. The network helps show where Erik Glatt may publish in the future.

Co-authorship network of co-authors of Erik Glatt

This figure shows the co-authorship network connecting the top 25 collaborators of Erik Glatt. A scholar is included among the top collaborators of Erik Glatt 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 Erik Glatt. Erik Glatt is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Glatt, Erik, et al.. (2025). Digital fiber length determination for injection molded glass fiber reinforced composite materials. e-Journal of Nondestructive Testing. 30(2).
2.
Weber, Matthias, et al.. (2024). Investigating Microstructure–Property Relationships of Nonwovens by Model-Based Virtual Material Testing. Transport in Porous Media. 151(6). 1403–1421. 3 indexed citations
3.
Glatt, Erik, et al.. (2024). Deep learning based segmentation of binder and fibers in gas diffusion layers. SHILAP Revista de lepidopterología. 6. 100411–100411. 2 indexed citations
4.
Weber, Matthias, et al.. (2023). Copula-based modeling and simulation of 3D systems of curved fibers by isolating intrinsic fiber properties and external effects. Scientific Reports. 13(1). 19359–19359. 2 indexed citations
5.
Glatt, Erik, et al.. (2022). Identification and analysis of fibers in ultra-large micro-CT scans of nonwoven textiles using deep learning. Journal of the Textile Institute. 114(11). 1647–1657. 6 indexed citations
6.
Schwarz, Jens-Oliver, et al.. (2019). Grain and pore shape analysis and generation of digital twins from digital images. e-Journal of Nondestructive Testing. 24(3). 1 indexed citations
7.
Schneider, Matti, Matthias Kabel, Heiko Andrä, et al.. (2016). Thermal fiber orientation tensors for digital paper physics. International Journal of Solids and Structures. 100-101. 234–244. 7 indexed citations
8.
Burton, Robert C., et al.. (2015). Sand Control Screen Erosion: Prediction and Avoidance. SPE Annual Technical Conference and Exhibition. 27 indexed citations
9.
Andrä, Heiko, Nicolas Combaret, Jack Dvorkin, et al.. (2012). Digital rock physics benchmarks—Part I: Imaging and segmentation. Computers & Geosciences. 50. 25–32. 552 indexed citations breakdown →
10.
Andrä, Heiko, Nicolas Combaret, Jack Dvorkin, et al.. (2012). Digital rock physics benchmarks—part II: Computing effective properties. Computers & Geosciences. 50. 33–43. 460 indexed citations breakdown →
11.
Mark, Andreas, Fredrik Edelvik, Erik Glatt, et al.. (2011). Multi-scale simulation of paperboard edge wicking using a fiber-resolving virtual paper model. Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft). 1 indexed citations
12.
Andrä, Heiko, Fredrik Edelvik, Erik Glatt, et al.. (2011). Micromechanical network model for the evaluation of quality controls of paper. Aerospace Medicine and Human Performance. 94(8). 49–55. 1 indexed citations
13.
Mark, Andreas, Fredrik Edelvik, Erik Glatt, et al.. (2011). Microstructure simulation of early paper forming using immersed boundary methods. TAPPI Journal. 11(11). 23–30. 6 indexed citations
14.
Cherif, C., et al.. (2011). MODELING AND CFD-SIMULATION OF WOVEN TEXTILES TO DETERMINE PERMEABILITY AND RETENTION PROPERTIES. Autex Research Journal. 11(3). 78–83. 19 indexed citations
15.
Glatt, Erik, et al.. (2008). Delay-sustained pattern formation in subexcitable media. Physical Review E. 77(6). 66220–66220. 12 indexed citations
16.
Glatt, Erik, et al.. (2007). Variability-sustained pattern formation in subexcitable media. Physical Review E. 75(2). 26206–26206. 33 indexed citations
17.
Glatt, Erik, et al.. (2007). Doubly diversity-induced resonance. Physical Review E. 76(1). 16203–16203. 39 indexed citations
18.
Glatt, Erik, et al.. (2007). Suppression of global oscillations via time-delayed feedback in a net of neural elements. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 6602. 660213–660213. 1 indexed citations
19.
Glatt, Erik, Hauke Busch, Friedemann Kaiser, & Alexey Zaikin. (2006). Noise-memory induced excitability and pattern formation in oscillatory neural models. Physical Review E. 73(2). 26216–26216. 16 indexed citations
20.
Glatt, Erik, et al.. (2006). Variability-induced transition in a net of neural elements: From oscillatory to excitable behavior. Physical Review E. 73(6). 66230–66230. 17 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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