Tuhin Chakrabarty
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 10%
- Experimental and Cognitive Psychology
- Information Systems top 10%
- Sociology and Political Science
- Co-authors
- Smaranda MuresanNanyun PengChristopher HideyKathy McKeownRalph WeischedelThomas ScialomVishakh PadmakumarPhilippe Laban
- Topics
- Topic Modeling (23 papers)Natural Language Processing Techniques (19 papers)Multimodal Machine Learning Applications (11 papers)
- Journals
- Scientific DataTransactions of the Association for Computational LinguisticsRare & Special e-Zone (The Hong Kong University of Science and Technology)
- Partner nations
- United StatesUnited KingdomCanada
In The Last Decade
Tuhin Chakrabarty
28 papers receiving 418 citations
Hit Papers
Peers
Comparison fields: 5 of 64
- Artificial Intelligence 337
- Computer Vision and Pattern Recognition 97
- Experimental and Cognitive Psychology 54
- Information Systems 47
- Sociology and Political Science 26
Countries citing papers authored by Tuhin Chakrabarty
This map shows the geographic impact of Tuhin Chakrabarty'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 Tuhin Chakrabarty with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tuhin Chakrabarty more than expected).
Fields of papers citing papers by Tuhin Chakrabarty
This network shows the impact of papers produced by Tuhin Chakrabarty. 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 Tuhin Chakrabarty. The network helps show where Tuhin Chakrabarty may publish in the future.
Co-authorship network of co-authors of Tuhin Chakrabarty
This figure shows the co-authorship network connecting the top 25 collaborators of Tuhin Chakrabarty. A scholar is included among the top collaborators of Tuhin Chakrabarty based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Tuhin Chakrabarty. Tuhin Chakrabarty is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 11 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 16 | |
| 6 | 1 | |
| 7 | 11 | |
| 8 | 7 | |
| 9 | 1 | |
| 10 | 2 | |
| 11 | 29 | |
| 12 | 19 | |
| 13 | 18 | |
| 14 | 34 | |
| 15 | 6 | |
| 16 | 2 | |
| 17 | 27 | |
| 18 | 61 | |
| 19 | 18 | |
| 20 | 13 |
About Tuhin Chakrabarty
Tuhin Chakrabarty is a scholar working on Artificial Intelligence, General Social Sciences and Computer Vision and Pattern Recognition, having authored 30 papers that have together received 433 indexed citations. Recurring topics across this work include Topic Modeling (23 papers), Natural Language Processing Techniques (19 papers) and Multimodal Machine Learning Applications (11 papers). The work is most often cited by research in Artificial Intelligence (337 citations), Health Informatics (10 citations) and General Social Sciences (17 citations). Tuhin Chakrabarty has collaborated with scholars based in United States, United Kingdom and Canada. Frequent co-authors include Smaranda Muresan, Nanyun Peng, Christopher Hidey, Kathy McKeown, Ralph Weischedel, Thomas Scialom, Vishakh Padmakumar, Philippe Laban, Xurui Zhang and Chien-Sheng Wu. Their work appears in journals such as Scientific Data, Transactions of the Association for Computational Linguistics and Rare & Special e-Zone (The Hong Kong University of Science and Technology).
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.