Gabriel Krummenacher
- Mechanical Engineering
- Industrial and Manufacturing Engineering top 5%
- Civil and Structural Engineering
- Computer Vision and Pattern Recognition
- Cognitive Neuroscience
- Co-authors
- Joachim M. BuhmannCheng Soon OngJörg StellingAlberto Giovanni BusettoDaniela NoaínSteven A. BrownAndrea SpinnlerChristian R. Baumann
- Topics
- Sparse and Compressive Sensing Techniques (1 paper)Neural Networks and Applications (1 paper)Advanced Multi-Objective Optimization Algorithms (1 paper)
- Journals
- BioinformaticsPLoS Computational BiologyIEEE Transactions on Intelligent Transportation Systems
- Partner nations
- SwitzerlandAustraliaGermany
In The Last Decade
Gabriel Krummenacher
6 papers receiving 289 citations
Peers
Comparison fields: 5 of 71
- Mechanical Engineering 104
- Industrial and Manufacturing Engineering 78
- Civil and Structural Engineering 61
- Computer Vision and Pattern Recognition 50
- Cognitive Neuroscience 48
Countries citing papers authored by Gabriel Krummenacher
This map shows the geographic impact of Gabriel Krummenacher'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 Gabriel Krummenacher with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gabriel Krummenacher more than expected).
Fields of papers citing papers by Gabriel Krummenacher
This network shows the impact of papers produced by Gabriel Krummenacher. 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 Gabriel Krummenacher. The network helps show where Gabriel Krummenacher may publish in the future.
Co-authorship network of co-authors of Gabriel Krummenacher
This figure shows the co-authorship network connecting the top 25 collaborators of Gabriel Krummenacher. A scholar is included among the top collaborators of Gabriel Krummenacher 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 Gabriel Krummenacher. Gabriel Krummenacher is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 51 | |
| 2 | 194 | |
| 3 | 3 | |
| 4 | 10 | |
| 5 | Ellipsoidal Multiple Instance Learning | 10 |
| 6 | 30 |
About Gabriel Krummenacher
Gabriel Krummenacher is a scholar working on Statistics and Probability, Media Technology and Signal Processing, having authored 6 papers that have together received 298 indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (1 paper), Neural Networks and Applications (1 paper) and Advanced Multi-Objective Optimization Algorithms (1 paper). The work is most often cited by research in Industrial and Manufacturing Engineering (78 citations), Media Technology (29 citations) and Civil and Structural Engineering (61 citations). Gabriel Krummenacher has collaborated with scholars based in Switzerland, Australia and Germany. Frequent co-authors include Joachim M. Buhmann, Cheng Soon Ong, Jörg Stelling, Alberto Giovanni Busetto, Daniela Noaín, Steven A. Brown, Andrea Spinnler, Christian R. Baumann, Sotiris Dimopoulos and Mojtaba Bandarabadi. Their work appears in journals such as Bioinformatics, PLoS Computational Biology and IEEE Transactions on Intelligent Transportation Systems.
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.