Ivan Dokmanić
- Signal Processing top 2%
- Electrical and Electronic Engineering top 10%
- Computational Mechanics top 5%
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition top 5%
- Co-authors
- Martin VetterliReza ParhizkarJuri RanieriSanja TomićYue M. LuMile ŠikićAndreas WaltherRobin Scheibler
- Topics
- Speech and Audio Processing (19 papers)Indoor and Outdoor Localization Technologies (17 papers)Sparse and Compressive Sensing Techniques (12 papers)
- Journals
- Proceedings of the National Academy of SciencesIEEE Transactions on Pattern Analysis and Machine IntelligenceIEEE Transactions on Signal Processing
- Partner nations
- SwitzerlandUnited StatesFrance
In The Last Decade
Ivan Dokmanić
54 papers receiving 1.2k citations
Hit Papers
Peers
Comparison fields: 5 of 148
- Signal Processing 419
- Electrical and Electronic Engineering 411
- Computational Mechanics 232
- Artificial Intelligence 180
- Computer Vision and Pattern Recognition 166
Countries citing papers authored by Ivan Dokmanić
This map shows the geographic impact of Ivan Dokmanić'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 Ivan Dokmanić with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ivan Dokmanić more than expected).
Fields of papers citing papers by Ivan Dokmanić
This network shows the impact of papers produced by Ivan Dokmanić. 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 Ivan Dokmanić. The network helps show where Ivan Dokmanić may publish in the future.
Co-authorship network of co-authors of Ivan Dokmanić
This figure shows the co-authorship network connecting the top 25 collaborators of Ivan Dokmanić. A scholar is included among the top collaborators of Ivan Dokmanić 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 Ivan Dokmanić. Ivan Dokmanić is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 3 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 3 | |
| 6 | 1 | |
| 7 | 4 | |
| 8 | 1 | |
| 9 | 5 | |
| 10 | Random mesh projectors for inverse problems | 5 |
| 11 | 2 | |
| 12 | 3 | |
| 13 | 52 | |
| 14 | Look, no beacons! Optimal all-in-one EchoSLAM | 4 |
| 15 | 3 | |
| 16 | OMP with Unknown Filters for Multipath Channel Estimation | 3 |
| 17 | 166 | |
| 18 | 13 | |
| 19 | 61 | |
| 20 | 196 |
About Ivan Dokmanić
Ivan Dokmanić is a scholar working on Structural Biology, Signal Processing and Computational Mathematics, having authored 58 papers that have together received 1.3k indexed citations. Recurring topics across this work include Speech and Audio Processing (19 papers), Indoor and Outdoor Localization Technologies (17 papers) and Sparse and Compressive Sensing Techniques (12 papers). The work is most often cited by research in Signal Processing (419 citations), Computational Mechanics (232 citations) and Acoustics and Ultrasonics (9 citations). Ivan Dokmanić has collaborated with scholars based in Switzerland, United States and France. Frequent co-authors include Martin Vetterli, Reza Parhizkar, Juri Ranieri, Sanja Tomić, Yue M. Lu, Mile Šikić, Andreas Walther, Robin Scheibler, Laurent Daudet and Sidharth Gupta. Their work appears in journals such as Proceedings of the National Academy of Sciences, IEEE Transactions on Pattern Analysis and Machine Intelligence and IEEE Transactions on Signal Processing.
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.