Rohan Kumar Das
Impact in
- Signal Processing top 0.5%
- Speech and Audio Processing
- Music and Audio Processing
- Artificial Intelligence top 1%
- Speech Recognition and Synthesis
- Natural Language Processing Techniques
- Speech and dialogue systems
Papers in
-
- Speech Recognition and Synthesis 84
- Natural Language Processing Techniques 12
- Speech and dialogue systems 6
-
- Speech and Audio Processing 75
- Music and Audio Processing 62
- Co-authors
- Haizhou Li (40 shared papers)Jichen Yang (14 shared papers)S. R. Mahadeva Prasanna (32 shared papers)Rohit Sinha (9 shared papers)Xiaohai Tian (8 shared papers)Ruijie Tao (6 shared papers)Kong Aik Lee (5 shared papers)Yi Zhou (5 shared papers)
In The Last Decade
Rohan Kumar Das
95 papers receiving 1.4k citations
Peers
Comparison fields: 5 of 76
- Signal Processing 1.2k
- Artificial Intelligence 1.2k
- Computer Vision and Pattern Recognition 280
- Pharmacy 60
- Physiology 83
Countries citing papers authored by Rohan Kumar Das
This map shows the geographic impact of Rohan Kumar Das'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 Rohan Kumar Das with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rohan Kumar Das more than expected).
Fields of papers citing papers by Rohan Kumar Das
This network shows the impact of papers produced by Rohan Kumar Das. 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 Rohan Kumar Das. The network helps show where Rohan Kumar Das may publish in the future.
Co-authors
The 25 scholars most cited alongside Rohan Kumar Das, 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 109 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 78 | |
| 2 | 2017 | 64 | |
| 3 | 2020 | 62 | |
| 4 | 2014 | 62 | |
| 5 | 2019 | 50 | |
| 6 | 2019 | 50 | |
| 7 | 2019 | 48 | |
| 8 | 2020 | 44 | |
| 9 | 2022 | 43 | |
| 10 | 2019 | 41 | |
| 11 | 2018 | 40 | |
| 12 | 2016 | 38 | |
| 13 | 2019 | 36 | |
| 14 | 2019 | 35 | |
| 15 | 2012 | 34 | |
| 16 | 2021 | 32 | |
| 17 | 2019 | 31 | |
| 18 | 2019 | 31 | |
| 19 | 2022 | 30 | |
| 20 | 2017 | 29 |
About Rohan Kumar Das
Rohan Kumar Das is a scholar working on Artificial Intelligence, Signal Processing, Computer Vision and Pattern Recognition, Pharmacy and Information Systems, having authored 109 papers that have together received 1.5k indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (84 papers), Speech and Audio Processing (75 papers), Music and Audio Processing (62 papers), Natural Language Processing Techniques (12 papers), Infant Health and Development (7 papers), Music Technology and Sound Studies (7 papers), Speech and dialogue systems (6 papers) and Digital Media Forensic Detection (4 papers). The work is most often cited by research in Signal Processing (1.2k citations), Artificial Intelligence (1.2k citations), Computer Vision and Pattern Recognition (280 citations), Pharmacy (60 citations) and Physiology (83 citations). Rohan Kumar Das has collaborated with scholars based in Singapore, India and China. Frequent co-authors include Haizhou Li, Jichen Yang, S. R. Mahadeva Prasanna, Rohit Sinha, Xiaohai Tian, Ruijie Tao, Kong Aik Lee, Yi Zhou, Mike Zheng Shou and Xinyuan Qian. Their work appears in journals such as International Journal of Speech Technology, IEEE/ACM Transactions on Audio Speech and Language Processing, IEEE Signal Processing Letters, Digital Signal Processing and IEEE Transactions on Information Forensics and Security.
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.