Michael Kraus

1.8k total citations · 1 hit paper
103 papers, 893 citations indexed

About

Michael Kraus is a scholar working on Mechanical Engineering, Civil and Structural Engineering and Sociology and Political Science. According to data from OpenAlex, Michael Kraus has authored 103 papers receiving a total of 893 indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Mechanical Engineering, 27 papers in Civil and Structural Engineering and 10 papers in Sociology and Political Science. Recurrent topics in Michael Kraus's work include Structural Analysis of Composite Materials (26 papers), Civil and Structural Engineering Research (11 papers) and Structural Health Monitoring Techniques (11 papers). Michael Kraus is often cited by papers focused on Structural Analysis of Composite Materials (26 papers), Civil and Structural Engineering Research (11 papers) and Structural Health Monitoring Techniques (11 papers). Michael Kraus collaborates with scholars based in Germany, Switzerland and United States. Michael Kraus's co-authors include Geralt Siebert, Jens Schneider, Michael Drass, A. Fußeder, Michael Fleming, J. Harry Isaacson, Marlon P. Mundt, Peter Hagedorn, Ha Thanh Le and Horst‐Michael Ludwig and has published in prestigious journals such as SHILAP Revista de lepidopterología, Construction and Building Materials and Physical Chemistry Chemical Physics.

In The Last Decade

Michael Kraus

84 papers receiving 778 citations

Hit Papers

Multi-Objective Loss Balancing for Physics-Informed Deep ... 2025 2026 2025 5 10 15 20 25
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.

  1. Multi-Objective Loss Balancing for Physics-Informed Deep Learning
    2025 26 citations Michael Kraus et al. Computer Methods in Applied Mechanics and Engineering profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Michael Kraus Germany 16 198 197 86 84 76 103 893
Edward Cohen United States 16 121 0.6× 851 4.3× 271 3.2× 54 0.6× 148 1.9× 95 1.9k
Giovanni Formica Italy 19 110 0.6× 330 1.7× 91 1.1× 263 3.1× 34 0.4× 55 985
Kathleen Trustrum United Kingdom 9 317 1.6× 216 1.1× 55 0.6× 248 3.0× 76 1.0× 15 1.3k
Saeed Karimi Iran 19 132 0.7× 110 0.6× 44 0.5× 143 1.7× 8 0.1× 135 1.3k
Carlos F. Lange Canada 23 158 0.8× 17 0.1× 36 0.4× 28 0.3× 52 0.7× 78 1.9k
Peter Moss New Zealand 22 186 0.9× 1.2k 6.3× 535 6.2× 37 0.4× 243 3.2× 103 2.0k
Thomas Götz Germany 18 48 0.2× 365 1.9× 158 1.8× 96 1.1× 40 0.5× 81 1.3k
Tsutomu Suzuki Japan 19 142 0.7× 21 0.1× 139 1.6× 180 2.1× 51 0.7× 158 1.2k
Kyungsik Kim South Korea 17 92 0.5× 253 1.3× 60 0.7× 8 0.1× 117 1.5× 105 1.0k
Pierre Charrier France 21 311 1.6× 168 0.9× 55 0.6× 95 1.1× 21 0.3× 67 1.7k

Countries citing papers authored by Michael Kraus

Since Specialization
Citations

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

Fields of papers citing papers by Michael Kraus

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michael Kraus

This figure shows the co-authorship network connecting the top 25 collaborators of Michael Kraus. A scholar is included among the top collaborators of Michael Kraus 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 Kraus. Michael Kraus 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.
Kraus, Michael, et al.. (2025). Key parameters for the non-destructive quality control of thermally toughened safety glass. Journal of Building Engineering. 106. 112613–112613.
2.
Kraus, Michael, et al.. (2025). Multi-Objective Loss Balancing for Physics-Informed Deep Learning. Computer Methods in Applied Mechanics and Engineering. 439. 117914–117914. 26 indexed citations breakdown →
3.
Kühn, S., et al.. (2025). Predictive structural assessment with Bayesian deep learning. Advanced Engineering Informatics. 68. 103721–103721.
4.
Kühn, S., et al.. (2024). Design Space Exploration and Explanation via Conditional Variational Autoencoders in Meta-Model-Based Conceptual Design of Pedestrian Bridges. Automation in Construction. 163. 105411–105411. 11 indexed citations
5.
Kraus, Michael, et al.. (2024). Grammar-based generation of strut-and-tie models for designing reinforced concrete structures. Computers & Structures. 305. 107549–107549.
6.
Kraus, Michael, et al.. (2024). Strength Lab AI: a mixture-of-experts deep learning approach for limit state analysis and design of monolithic and laminate structures made of glass. Glass Structures & Engineering. 9(3-4). 607–655. 2 indexed citations
7.
Drass, Michael, et al.. (2023). Temp-AI-Estimator: Interior temperature prediction using domain-informed Deep Learning. Energy and Buildings. 297. 113425–113425. 2 indexed citations
8.
9.
Kraus, Michael, et al.. (2023). Urban airflow prediction by pix2pix trained on FFD. Journal of Physics Conference Series. 2600(8). 82009–82009. 1 indexed citations
10.
Kocer, Cenk, et al.. (2022). Automated quality control of vacuum insulated glazing by convolutional neural network image classification. Automation in Construction. 135. 104144–104144. 13 indexed citations
11.
Guinsburg, Adrián, Yue Jiao, Caitlin Monaghan, et al.. (2022). Predictors of shorter- and longer-term mortality after COVID-19 presentation among dialysis patients: parallel use of machine learning models in Latin and North American countries. BMC Nephrology. 23(1). 340–340. 2 indexed citations
12.
Kraus, Michael, et al.. (2018). Sensitivity analysis for the determination of the interlayer shear modulus in laminated glass using a torsional test. Glass Structures & Engineering. 3(2). 355–371. 4 indexed citations
13.
14.
Kraus, Michael, et al.. (2018). Objetos como testigos del contacto cultural: perspectivas interculturales de la historia y del presente de las poblaciones indígenas del alto río Negro (Brasil/Colombia). 11. 2 indexed citations
15.
Kraus, Michael. (2010). De la teoría al indio. Experiencias de investigación de Theodor Koch-Grünberg. SHILAP Revista de lepidopterología. 13–36.
16.
Burress, Jacob, Michael Kraus, Matthew Beckner, et al.. (2009). Hydrogen storage in engineered carbon nanospaces. Nanotechnology. 20(20). 204026–204026. 67 indexed citations
17.
Kraus, Michael, et al.. (2004). Die Xingu-Expedition (1898-1900) : ein Forschungstagebuch. Böhlau eBooks. 2 indexed citations
18.
Kraus, Michael, et al.. (2000). Irreconcilable differences? : explaining Czechoslovakia's dissolution. Rowman & Littlefield eBooks. 8 indexed citations
19.
Kraus, Michael, et al.. (1993). Jonny spielt auf : Oper in zwei Teilen.
20.
Kraus, Michael. (1957). The North Atlantic civilization. 4 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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