Philippe Tillet
Impact in
- Computational Mathematics top 10%
- Tensor decomposition and applications
- Hardware and Architecture top 5%
- Parallel Computing and Optimization Techniques
Papers in
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- Parallel Computing and Optimization Techniques 4
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- Advanced Data Storage Technologies 1
- Interconnection Networks and Systems 1
- Co-authors
- David Cox (2 shared papers)H. T. Kung (1 shared paper)Karl Rupp (3 shared papers)S. Selberherr (3 shared papers)Tibor Grasser (1 shared paper)Ansgar Jüngel (1 shared paper)Josef Weinbub (1 shared paper)Chin‐Teng Lin (1 shared paper)
- Journals
- SIAM Journal on Scientific Computing (1 paper)IEEE International Conference on High Performance Computing, Data, and Analytics (1 paper)
- Partner nations
- United StatesAustriaTaiwan
In The Last Decade
Philippe Tillet
5 papers receiving 183 citations
Peers
Comparison fields: 5 of 46
- Computational Mathematics 17
- Hardware and Architecture 84
- Computer Networks and Communications 53
- Computer Vision and Pattern Recognition 46
- Computer Graphics and Computer-Aided Design 6
Countries citing papers authored by Philippe Tillet
This map shows the geographic impact of Philippe Tillet'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 Philippe Tillet with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Philippe Tillet more than expected).
Fields of papers citing papers by Philippe Tillet
This network shows the impact of papers produced by Philippe Tillet. 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 Philippe Tillet. The network helps show where Philippe Tillet may publish in the future.
Co-authors
The 9 scholars most cited alongside Philippe Tillet, 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 | 106 | |
| 2 | 2016 | 58 | |
| 3 | 2013 | 13 | |
| 4 | 2012 | 9 | |
| 5 | 2017 | 4 |
About Philippe Tillet
Philippe Tillet is a scholar working on Hardware and Architecture, Computer Networks and Communications, Computational Mechanics, Computational Theory and Mathematics and Information Systems, having authored 5 papers that have together received 190 indexed citations. Recurring topics across this work include Parallel Computing and Optimization Techniques (4 papers), Matrix Theory and Algorithms (2 papers), Advanced Data Storage Technologies (1 paper), Cloud Computing and Resource Management (1 paper), Blind Source Separation Techniques (1 paper), Interconnection Networks and Systems (1 paper), Neural Networks and Applications (1 paper) and Advanced Numerical Methods in Computational Mathematics (1 paper). The work is most often cited by research in Computational Mathematics (17 citations), Hardware and Architecture (84 citations), Computer Networks and Communications (53 citations), Computer Vision and Pattern Recognition (46 citations) and Computer Graphics and Computer-Aided Design (6 citations). Philippe Tillet has collaborated with scholars based in United States, Austria and Taiwan. Frequent co-authors include David Cox, H. T. Kung, Karl Rupp, S. Selberherr, Tibor Grasser, Ansgar Jüngel, Josef Weinbub, Chin‐Teng Lin and H. T. Kung. Their work appears in journals such as SIAM Journal on Scientific Computing and IEEE International Conference on High Performance Computing, Data, and Analytics.
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.