Dan Kushnir
Impact in
- Signal Processing top 10%
- Speech and Audio Processing
- Marketing top 10%
- Customer churn and segmentation
Papers in
-
- Advanced Clustering Algorithms Research 2
- Anomaly Detection Techniques and Applications 2
- Machine Learning and Algorithms 2
-
- Software System Performance and Reliability 2
- Co-authors
- Achi Brandt (3 shared papers)Ronald R. Coifman (3 shared papers)Meirav Galun (2 shared papers)Veena Mendiratta (2 shared papers)Hüseyin Uzunalioğlu (3 shared papers)Derek Doran (1 shared paper)Sharon Gannot (1 shared paper)Israel Cohen (1 shared paper)
- Journals
- Applied and Computational Harmonic Analysis (2 papers)Physical Review Letters (1 paper)Pattern Recognition (1 paper)IEEE Transactions on Signal Processing (1 paper)IEEE Transactions on Pattern Analysis and Machine Intelligence (1 paper)
- Partner nations
- United StatesIsraelGermany
In The Last Decade
Dan Kushnir
14 papers receiving 283 citations
Peers
Comparison fields: 5 of 42
- Signal Processing 36
- Marketing 36
- Computational Mathematics 2
- Computational Theory and Mathematics 52
- Statistical and Nonlinear Physics 28
Countries citing papers authored by Dan Kushnir
This map shows the geographic impact of Dan Kushnir'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 Dan Kushnir with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dan Kushnir more than expected).
Fields of papers citing papers by Dan Kushnir
This network shows the impact of papers produced by Dan Kushnir. 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 Dan Kushnir. The network helps show where Dan Kushnir may publish in the future.
Co-authors
The 14 scholars most cited alongside Dan Kushnir, 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 | 2006 | 51 | |
| 2 | 2011 | 50 | |
| 3 | 2013 | 50 | |
| 4 | 2011 | 42 | |
| 5 | 2009 | 25 | |
| 6 | 2006 | 19 | |
| 7 | 2013 | 18 | |
| 8 | 2017 | 12 | |
| 9 | 2016 | 10 | |
| 10 | 2014 | 7 | |
| 11 | 2018 | 4 | |
| 12 | 2015 | 1 | |
| 13 | Towards Clustering High-dimensional Gaussian Mixture Clouds in Linear Running Time | 2019 | 1 |
| 14 | 2023 | 1 |
About Dan Kushnir
Dan Kushnir is a scholar working on Artificial Intelligence, Computer Networks and Communications, Signal Processing, Marketing and Computational Theory and Mathematics, having authored 14 papers that have together received 291 indexed citations. Recurring topics across this work include Blind Source Separation Techniques (2 papers), Advanced Clustering Algorithms Research (2 papers), Anomaly Detection Techniques and Applications (2 papers), Customer churn and segmentation (2 papers), Software System Performance and Reliability (2 papers), Machine Learning and Algorithms (2 papers), Control Systems and Identification (1 paper) and Topological and Geometric Data Analysis (1 paper). The work is most often cited by research in Signal Processing (36 citations), Marketing (36 citations), Computational Mathematics (2 citations), Computational Theory and Mathematics (52 citations) and Statistical and Nonlinear Physics (28 citations). Dan Kushnir has collaborated with scholars based in United States, Israel and Germany. Frequent co-authors include Achi Brandt, Ronald R. Coifman, Meirav Galun, Veena Mendiratta, Hüseyin Uzunalioğlu, Derek Doran, Sharon Gannot, Israel Cohen, Ronen Talmon and Jörg Schumacher. Their work appears in journals such as Applied and Computational Harmonic Analysis, Physical Review Letters, Pattern Recognition, IEEE Transactions on Signal Processing and IEEE Transactions on Pattern Analysis and Machine Intelligence.
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.