Akash Kumar Mohankumar
Impact in
- Health Informatics top 10%
- Artificial Intelligence in Healthcare and Education
- Artificial Intelligence top 5%
- Topic Modeling
- Natural Language Processing Techniques
- Speech and dialogue systems
- Explainable Artificial Intelligence (XAI)
Papers in
-
- Natural Language Processing Techniques 3
- Topic Modeling 1
- Speech and dialogue systems 1
- Explainable Artificial Intelligence (XAI) 1
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- Information Retrieval and Search Behavior 3
- Co-authors
- Mitesh M. Khapra (5 shared papers)Preksha Nema (2 shared papers)Balaraman Ravindran (2 shared papers)Balaji Vasan Srinivasan (2 shared papers)Amit Kumar Singh (1 shared paper)
- Journals
- Transactions of the Association for Computational Linguistics (1 paper)ACM Computing Surveys (1 paper)arXiv (Cornell University) (1 paper)ACM International Conference on Information and Knowledge Management (CIKM) (1 paper)Conference on Empirical Methods in Natural Language Processing: Industry Track (EMNLP) (1 paper)
- Partner nations
- IndiaUnited States
In The Last Decade
Akash Kumar Mohankumar
8 papers receiving 275 citations
Peers
Comparison fields: 5 of 33
- Health Informatics 18
- Artificial Intelligence 211
- Information Systems 40
- Computer Vision and Pattern Recognition 22
- Safety Research 6
Countries citing papers authored by Akash Kumar Mohankumar
This map shows the geographic impact of Akash Kumar Mohankumar'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 Akash Kumar Mohankumar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Akash Kumar Mohankumar more than expected).
Fields of papers citing papers by Akash Kumar Mohankumar
This network shows the impact of papers produced by Akash Kumar Mohankumar. 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 Akash Kumar Mohankumar. The network helps show where Akash Kumar Mohankumar may publish in the future.
Co-authors
The 5 scholars most cited alongside Akash Kumar Mohankumar, 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 | 2022 | 115 | |
| 2 | 2020 | 61 | |
| 3 | 2020 | 45 | |
| 4 | 2019 | 41 | |
| 5 | 2021 | 12 | |
| 6 | 2022 | 4 | |
| 7 | 2023 | 2 | |
| 8 | 2024 | 1 |
About Akash Kumar Mohankumar
Akash Kumar Mohankumar is a scholar working on Artificial Intelligence, Information Systems, Management Science and Operations Research, Nuclear Energy and Engineering and Waste Management and Disposal, having authored 8 papers that have together received 281 indexed citations. Recurring topics across this work include Information Retrieval and Search Behavior (3 papers), Natural Language Processing Techniques (3 papers), Topic Modeling (1 paper), Advanced Bandit Algorithms Research (1 paper), Speech and dialogue systems (1 paper) and Explainable Artificial Intelligence (XAI) (1 paper). The work is most often cited by research in Health Informatics (18 citations), Artificial Intelligence (211 citations), Information Systems (40 citations), Computer Vision and Pattern Recognition (22 citations) and Safety Research (6 citations). Akash Kumar Mohankumar has collaborated with scholars based in India and United States. Frequent co-authors include Mitesh M. Khapra, Preksha Nema, Balaraman Ravindran, Balaji Vasan Srinivasan and Amit Kumar Singh. Their work appears in journals such as Transactions of the Association for Computational Linguistics, ACM Computing Surveys, arXiv (Cornell University), ACM International Conference on Information and Knowledge Management (CIKM) and Conference on Empirical Methods in Natural Language Processing: Industry Track (EMNLP).
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.