Anhad Mohananey
Impact in
- Artificial Intelligence top 10%
- Topic Modeling
- Natural Language Processing Techniques
- Text Readability and Simplification
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- Opportunistic and Delay-Tolerant Networks
- Mobile Ad Hoc Networks
- Caching and Content Delivery
Papers in
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- Topic Modeling 4
- Natural Language Processing Techniques 4
- Speech and dialogue systems 2
- Text Readability and Simplification 1
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- Caching and Content Delivery 1
- Opportunistic and Delay-Tolerant Networks 1
- Mobile Ad Hoc Networks 1
- Co-authors
- Samuel R. Bowman (3 shared papers)Alicia Parrish (2 shared papers)Wei Peng (2 shared papers)Alex Warstadt (2 shared papers)Sheng‐Fu Wang (2 shared papers)Haokun Liu (2 shared papers)Sanjay Kumar Dhurandher (1 shared paper)Isaac Woungang (1 shared paper)
- Journals
- IEEE Systems Journal (1 paper)Faculty Digital Archive (New York University Florence) (2 papers)
- Partner nations
- United StatesIndiaCanada
In The Last Decade
Anhad Mohananey
5 papers receiving 304 citations
Peers
Comparison fields: 5 of 34
- Artificial Intelligence 192
- Computer Networks and Communications 99
- Computer Vision and Pattern Recognition 49
- Cognitive Neuroscience 28
- Cultural Studies 11
Countries citing papers authored by Anhad Mohananey
This map shows the geographic impact of Anhad Mohananey'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 Anhad Mohananey with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Anhad Mohananey more than expected).
Fields of papers citing papers by Anhad Mohananey
This network shows the impact of papers produced by Anhad Mohananey. 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 Anhad Mohananey. The network helps show where Anhad Mohananey may publish in the future.
Co-authors
The 19 scholars most cited alongside Anhad Mohananey, 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 | 2020 | 155 | |
| 2 | 2016 | 105 | |
| 3 | 2019 | 48 | |
| 4 | 2019 | 3 | |
| 5 | 2025 | 2 |
About Anhad Mohananey
Anhad Mohananey is a scholar working on Artificial Intelligence, Computer Networks and Communications, Infectious Diseases, Organic Chemistry and Surgery, having authored 5 papers that have together received 313 indexed citations. Recurring topics across this work include Topic Modeling (4 papers), Natural Language Processing Techniques (4 papers), Speech and dialogue systems (2 papers), Caching and Content Delivery (1 paper), Opportunistic and Delay-Tolerant Networks (1 paper), Text Readability and Simplification (1 paper) and Mobile Ad Hoc Networks (1 paper). The work is most often cited by research in Artificial Intelligence (192 citations), Computer Networks and Communications (99 citations), Computer Vision and Pattern Recognition (49 citations), Cognitive Neuroscience (28 citations) and Cultural Studies (11 citations). Anhad Mohananey has collaborated with scholars based in United States, India and Canada. Frequent co-authors include Samuel R. Bowman, Alicia Parrish, Wei Peng, Alex Warstadt, Sheng‐Fu Wang, Haokun Liu, Sanjay Kumar Dhurandher, Isaac Woungang, Deepak Kumar Sharma and Joel J. P. C. Rodrigues. Their work appears in journals such as IEEE Systems Journal and Faculty Digital Archive (New York University Florence).
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.