David Gunawan
Impact in
- Signal Processing top 10%
- Speech and Audio Processing
- Music and Audio Processing
- Blind Source Separation Techniques
- Statistics and Probability top 10%
- Statistical Methods and Bayesian Inference
- Statistical Methods and Inference
Papers in
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- Statistical Methods and Bayesian Inference 9
- Statistical Methods and Inference 6
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- Speech and Audio Processing 4
- Music and Audio Processing 4
- Co-authors
- Deeptanu Sen (4 shared papers)Robert Kohn (16 shared papers)Minh‐Ngoc Tran (8 shared papers)Jialun Chen (6 shared papers)Wenhua Zhao (6 shared papers)Ian A. Milne (6 shared papers)Paul H. Taylor (6 shared papers)William E. Griffiths (4 shared papers)
In The Last Decade
David Gunawan
36 papers receiving 215 citations
Peers
Comparison fields: 5 of 60
- Signal Processing 75
- Statistics and Probability 41
- General Decision Sciences 5
- Finance 21
- Oceanography 23
Countries citing papers authored by David Gunawan
This map shows the geographic impact of David Gunawan'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 David Gunawan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Gunawan more than expected).
Fields of papers citing papers by David Gunawan
This network shows the impact of papers produced by David Gunawan. 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 David Gunawan. The network helps show where David Gunawan may publish in the future.
Co-authors
The 25 scholars most cited alongside David Gunawan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 40 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2010 | 58 | |
| 2 | 2023 | 15 | |
| 3 | 2023 | 14 | |
| 4 | 2022 | 12 | |
| 5 | 2021 | 11 | |
| 6 | 2020 | 11 | |
| 7 | 2008 | 10 | |
| 8 | 2018 | 9 | |
| 9 | 2022 | 8 | |
| 10 | 2018 | 7 | |
| 11 | 2024 | 7 | |
| 12 | 2011 | 5 | |
| 13 | 2022 | 5 | |
| 14 | 2022 | 5 | |
| 15 | Separation of Harmonic Musical Instrument Notes Using Spectro-Temporal Modeling of Harmonic Magnitudes and Spectrogram Inversion with Phase Optimization | 2013 | 4 |
| 16 | 2020 | 4 | |
| 17 | 2020 | 4 | |
| 18 | 2006 | 3 | |
| 19 | 2020 | 3 | |
| 20 | 2020 | 3 |
About David Gunawan
David Gunawan is a scholar working on Statistics and Probability, Signal Processing, Economics and Econometrics, Oceanography and Management Science and Operations Research, having authored 40 papers that have together received 223 indexed citations. Recurring topics across this work include Statistical Methods and Bayesian Inference (9 papers), Bayesian Methods and Mixture Models (6 papers), Statistical Methods and Inference (6 papers), Ocean Waves and Remote Sensing (5 papers), Speech and Audio Processing (4 papers), Spatial and Panel Data Analysis (4 papers), Music and Audio Processing (4 papers) and Financial Risk and Volatility Modeling (4 papers). The work is most often cited by research in Signal Processing (75 citations), Statistics and Probability (41 citations), General Decision Sciences (5 citations), Finance (21 citations) and Oceanography (23 citations). David Gunawan has collaborated with scholars based in Australia, Germany and Indonesia. Frequent co-authors include Deeptanu Sen, Robert Kohn, Minh‐Ngoc Tran, Jialun Chen, Wenhua Zhao, Ian A. Milne, Paul H. Taylor, William E. Griffiths, Duangkamon Chotikapanich and David John Nott. Their work appears in journals such as Statistics and Computing, Ocean Engineering, Journal of the Audio Engineering Society, Journal of Business and Economic Statistics and Behavior Research Methods.
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.