Mohit Kumar
Impact in
- Signal Processing top 10%
- Speech and Audio Processing
- Music and Audio Processing
- Artificial Intelligence top 10%
- Speech Recognition and Synthesis
- Speech and dialogue systems
- Natural Language Processing Techniques
- Topic Modeling
Papers in
-
- Topic Modeling 5
- Natural Language Processing Techniques 5
- AI-based Problem Solving and Planning 4
- Advanced Text Analysis Techniques 3
- Speech and dialogue systems 3
- Semantic Web and Ontologies 2
-
- Constraint Satisfaction and Optimization 4
- Co-authors
- Alexander I. Rudnicky (6 shared papers)Alan W. Black (1 shared paper)A.C.K. Chan (1 shared paper)Mosur Ravishankar (1 shared paper)David Huggins-Daines (1 shared paper)Dipanjan Das (3 shared papers)Stefano Teso (4 shared papers)Luc De Raedt (4 shared papers)
- Journals
- PeerJ Computer Science (1 paper)Artificial Intelligence (1 paper)International Journal of Electronics (1 paper)Figshare (2 papers)Lirias (1 paper)
- Partner nations
- United StatesBelgiumIndia
In The Last Decade
Mohit Kumar
15 papers receiving 339 citations
Peers
Comparison fields: 5 of 65
- Signal Processing 105
- Artificial Intelligence 210
- Human-Computer Interaction 27
- Computer Vision and Pattern Recognition 81
- Computer Networks and Communications 47
Countries citing papers authored by Mohit Kumar
This map shows the geographic impact of Mohit Kumar'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 Mohit Kumar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mohit Kumar more than expected).
Fields of papers citing papers by Mohit Kumar
This network shows the impact of papers produced by Mohit Kumar. 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 Mohit Kumar. The network helps show where Mohit Kumar may publish in the future.
Co-authors
The 15 scholars most cited alongside Mohit Kumar, 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 | 331 | |
| 2 | 2009 | 8 | |
| 3 | 2016 | 5 | |
| 4 | 2019 | 5 | |
| 5 | Automatic Extraction of Briefing Templates | 2008 | 4 |
| 6 | Summarizing Non-textual Events with a 'Briefing' Focus | 2007 | 4 |
| 7 | 2025 | 3 | |
| 8 | 2015 | 3 | |
| 9 | 2020 | 3 | |
| 10 | 2018 | 2 | |
| 11 | 2020 | 2 | |
| 12 | 2021 | 2 | |
| 13 | 2022 | 2 | |
| 14 | 2018 | 1 | |
| 15 | 2006 | 1 |
About Mohit Kumar
Mohit Kumar is a scholar working on Artificial Intelligence, Computer Networks and Communications, Signal Processing, Computational Theory and Mathematics and Information Systems, having authored 15 papers that have together received 376 indexed citations. Recurring topics across this work include Topic Modeling (5 papers), Natural Language Processing Techniques (5 papers), AI-based Problem Solving and Planning (4 papers), Constraint Satisfaction and Optimization (4 papers), Advanced Text Analysis Techniques (3 papers), Speech and dialogue systems (3 papers), Digital Filter Design and Implementation (2 papers) and Semantic Web and Ontologies (2 papers). The work is most often cited by research in Signal Processing (105 citations), Artificial Intelligence (210 citations), Human-Computer Interaction (27 citations), Computer Vision and Pattern Recognition (81 citations) and Computer Networks and Communications (47 citations). Mohit Kumar has collaborated with scholars based in United States, Belgium and India. Frequent co-authors include Alexander I. Rudnicky, Alan W. Black, A.C.K. Chan, Mosur Ravishankar, David Huggins-Daines, Dipanjan Das, Stefano Teso, Luc De Raedt, Sachin Agarwal and Nikesh Garera. Their work appears in journals such as PeerJ Computer Science, Artificial Intelligence, International Journal of Electronics, Figshare and Lirias.
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.