Vaibhav Tripathi
- Artificial Intelligence top 10%
- Sentiment Analysis and Opinion Mining 4
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- Mental Health Research Topics 4
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- Functional Brain Connectivity Studies 10
- Neural dynamics and brain function 5
- EEG and Brain-Computer Interfaces 5
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- Advanced Neuroimaging Techniques and Applications 4
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- Hydrological Forecasting Using AI 3
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- Hydrology and Watershed Management Studies 3
- Co-authors
- Mark CarmanAditya JoshiPushpak BhattacharyyaPallavi BharadwajDavid C. SomersManas Ranjan PrustyMohit Prakash MohantyRahul Garg
- Journals
- Journal of Vision (2 papers)NeuroImage (2 papers)Biological Psychiatry Cognitive Neuroscience and Neuroimaging (2 papers)
- Partner nations
- United StatesIndiaAustralia
In The Last Decade
Vaibhav Tripathi
22 papers receiving 228 citations
Peers
Comparison fields: 5 of 53
- Artificial Intelligence 136
- Experimental and Cognitive Psychology 32
- Cognitive Neuroscience 44
- Clinical Psychology 32
- Computer Vision and Pattern Recognition 23
Countries citing papers authored by Vaibhav Tripathi
This map shows the geographic impact of Vaibhav Tripathi'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 Vaibhav Tripathi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Vaibhav Tripathi more than expected).
Fields of papers citing papers by Vaibhav Tripathi
This network shows the impact of papers produced by Vaibhav Tripathi. 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 Vaibhav Tripathi. The network helps show where Vaibhav Tripathi may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Vaibhav Tripathi, 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 | 2025 | 3 | |
| 2 | 2025 | 3 | |
| 3 | 2025 | 1 | |
| 4 | 2025 | 1 | |
| 5 | 2025 | 0 | |
| 6 | 2025 | 1 | |
| 7 | 2024 | 9 | |
| 8 | 2024 | 7 | |
| 9 | 2024 | 6 | |
| 10 | 2023 | 0 | |
| 11 | 2023 | 3 | |
| 12 | 2022 | 5 | |
| 13 | 2021 | 10 | |
| 14 | 2021 | 12 | |
| 15 | 2021 | 14 | |
| 16 | 2020 | 13 | |
| 17 | 2019 | 2 | |
| 18 | 2016 | 39 | |
| 19 | EmoGram: An Open-Source Time Sequence-Based Emotion Tracker and Its Innovative Applications | 2016 | 8 |
| 20 | 2016 | 94 |
About Vaibhav Tripathi
Vaibhav Tripathi is a scholar working on Cognitive Neuroscience, Experimental and Cognitive Psychology and Radiology, Nuclear Medicine and Imaging, having authored 24 papers that have together received 242 indexed citations. Recurring topics across this work include Functional Brain Connectivity Studies (10 papers), Neural dynamics and brain function (5 papers), EEG and Brain-Computer Interfaces (5 papers), Sentiment Analysis and Opinion Mining (4 papers), Advanced Neuroimaging Techniques and Applications (4 papers), Mental Health Research Topics (4 papers), Hydrological Forecasting Using AI (3 papers) and Hydrology and Watershed Management Studies (3 papers). The work is most often cited by research in Artificial Intelligence (136 citations), Experimental and Cognitive Psychology (32 citations) and Cognitive Neuroscience (44 citations). Vaibhav Tripathi has collaborated with scholars based in United States, India and Australia. Frequent co-authors include Mark Carman, Aditya Joshi, Pushpak Bhattacharyya, Pallavi Bharadwaj, David C. Somers, Manas Ranjan Prusty, Mohit Prakash Mohanty, Rahul Garg, Kathryn J. Devaney and Sara W. Lazar. Their work appears in journals such as Journal of Vision, NeuroImage, Biological Psychiatry Cognitive Neuroscience and Neuroimaging, Alzheimer s & Dementia and Scientific Reports.
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.