Max Schwarzer
Impact in
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- Infrastructure Maintenance and Monitoring
- Structural Health Monitoring Techniques
- Innovative concrete reinforcement materials
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- Numerical methods in engineering
- Rock Mechanics and Modeling
Papers in
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- Topic Modeling 2
- Text Readability and Simplification 1
- Natural Language Processing Techniques 1
- Reinforcement Learning in Robotics 1
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- Advanced Electron Microscopy Techniques and Applications 1
- Co-authors
- Viet T. Chau (1 shared paper)G. Srinivasan (1 shared paper)Hari Viswanathan (1 shared paper)Esteban Rougier (1 shared paper)Allon G. Percus (1 shared paper)Marc G. Bellemare (1 shared paper)Aaron Courville (2 shared papers)Maxim Ziatdinov (1 shared paper)
- Journals
- Computational Materials Science (1 paper)Microscopy and Microanalysis (1 paper)arXiv (Cornell University) (1 paper)
- Partner nations
- United StatesCanadaGermany
In The Last Decade
Max Schwarzer
2 papers receiving 66 citations
Peers
Comparison fields: 5 of 37
- Civil and Structural Engineering 23
- Mechanics of Materials 25
- Structural Biology 1
- Statistical and Nonlinear Physics 7
- Ocean Engineering 8
Countries citing papers authored by Max Schwarzer
This map shows the geographic impact of Max Schwarzer'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 Max Schwarzer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Max Schwarzer more than expected).
Fields of papers citing papers by Max Schwarzer
This network shows the impact of papers produced by Max Schwarzer. 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 Max Schwarzer. The network helps show where Max Schwarzer may publish in the future.
Co-authors
The 14 scholars most cited alongside Max Schwarzer, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 66 | |
| 2 | 2021 | 1 | |
| 3 | 2023 | 0 | |
| 4 | 2021 | 0 |
About Max Schwarzer
Max Schwarzer is a scholar working on Artificial Intelligence, Structural Biology, Civil and Structural Engineering, Computer Vision and Pattern Recognition and Mechanics of Materials, having authored 4 papers that have together received 67 indexed citations. Recurring topics across this work include Topic Modeling (2 papers), Text Readability and Simplification (1 paper), Infrastructure Maintenance and Monitoring (1 paper), Drilling and Well Engineering (1 paper), Natural Language Processing Techniques (1 paper), Advanced Electron Microscopy Techniques and Applications (1 paper), Reinforcement Learning in Robotics (1 paper) and Electron and X-Ray Spectroscopy Techniques (1 paper). The work is most often cited by research in Civil and Structural Engineering (23 citations), Mechanics of Materials (25 citations), Structural Biology (1 citation), Statistical and Nonlinear Physics (7 citations) and Ocean Engineering (8 citations). Max Schwarzer has collaborated with scholars based in United States, Canada and Germany. Frequent co-authors include Viet T. Chau, G. Srinivasan, Hari Viswanathan, Esteban Rougier, Allon G. Percus, Marc G. Bellemare, Aaron Courville, Maxim Ziatdinov, Igor Mordatch and Pablo Samuel Castro. Their work appears in journals such as Computational Materials Science, Microscopy and Microanalysis and arXiv (Cornell University).
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.