Gil Keren

699 citations
22 papers · 290 · h-index 11

Impact in

    • Speech and Audio Processing
    • Music and Audio Processing
    • Speech Recognition and Synthesis
    • Natural Language Processing Techniques
    • Topic Modeling
    • Anomaly Detection Techniques and Applications
    • Speech and dialogue systems

Papers in

    • Speech Recognition and Synthesis 13
    • Domain Adaptation and Few-Shot Learning 4
    • Adversarial Robustness in Machine Learning 2
    • Topic Modeling 2
    • Machine Learning and Data Classification 2
    • Speech and Audio Processing 11
    • Music and Audio Processing 9

Gil Keren

18 papers receiving 262 citations

Peers

Gil Keren
Comparison fields: 5 of 52
  • Signal Processing 138
  • Artificial Intelligence 202
  • Experimental and Cognitive Psychology 35
  • Computer Vision and Pattern Recognition 36
  • Acoustics and Ultrasonics 1
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Ali Ziaei United States
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Citations per field
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Citations per year

Countries citing papers authored by Gil Keren

Since Specialization
Citations

This map shows the geographic impact of Gil Keren'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 Gil Keren with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gil Keren more than expected).

Fields of papers citing papers by Gil Keren

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gil Keren. 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 Gil Keren. The network helps show where Gil Keren may publish in the future.

Co-authors

The 25 scholars most cited alongside Gil Keren, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Gil Keren Line = papers co-authored together Gil Keren links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202151
2 202147
3 201940
4 202126
5 201723
6 201817
7 201615
8 201813
9 202111
10 201810
11 201810
12 20176
13 20226
14 20214
15 20213
16 20233
17 20252
18 20192
19 20231
20 20250

About Gil Keren

Gil Keren is a scholar working on Artificial Intelligence, Signal Processing, Computer Vision and Pattern Recognition, Cognitive Neuroscience and Control and Systems Engineering, having authored 22 papers that have together received 290 indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (13 papers), Speech and Audio Processing (11 papers), Music and Audio Processing (9 papers), Domain Adaptation and Few-Shot Learning (4 papers), Adversarial Robustness in Machine Learning (2 papers), Topic Modeling (2 papers), Advanced Data Compression Techniques (2 papers) and Machine Learning and Data Classification (2 papers). The work is most often cited by research in Signal Processing (138 citations), Artificial Intelligence (202 citations), Experimental and Cognitive Psychology (35 citations), Computer Vision and Pattern Recognition (36 citations) and Acoustics and Ultrasonics (1 citation). Gil Keren has collaborated with scholars based in Germany, United Kingdom and Israel. Frequent co-authors include Björn W. Schuller, Christian Fuegen, Jay Mahadeokar, Duc Le, Michael L. Seltzer, Julian Chan, Nicholas Cummins, Ingmar Steiner, Andreas Triantafyllopoulos and Johannes Wagner. Their work appears in journals such as IEEE Access, Multimedia Tools and Applications, Knowledge and Information Systems, Acta acustica united with Acustica and Trends in Hearing.

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.

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