Jay Pujara
Impact in
- Artificial Intelligence top 2%
- Topic Modeling
- Natural Language Processing Techniques
- Advanced Graph Neural Networks
- Explainable Artificial Intelligence (XAI)
- Semantic Web and Ontologies
- Text and Document Classification Technologies
- Health Informatics top 10%
Papers in
-
- Topic Modeling 26
- Natural Language Processing Techniques 15
- Advanced Graph Neural Networks 10
- Semantic Web and Ontologies 9
- Speech and dialogue systems 5
- Data Stream Mining Techniques 5
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- Data Quality and Management 14
- Co-authors
- Lise Getoor (20 shared papers)Pigi Kouki (5 shared papers)John O’Donovan (3 shared papers)James Schaffer (3 shared papers)Xiang Ren (11 shared papers)Fred Morstatter (4 shared papers)Pedro Szekely (8 shared papers)Dong‐Ho Lee (7 shared papers)
- Journals
- Knowledge and Information Systems (2 papers)AI Magazine (1 paper)Proceedings of the National Academy of Sciences (1 paper)ACM Transactions on Interactive Intelligent Systems (1 paper)IEEE Transactions on Wireless Communications (1 paper)
- Partner nations
- United StatesIndiaGermany
In The Last Decade
Jay Pujara
60 papers receiving 710 citations
Peers
Comparison fields: 5 of 87
- Artificial Intelligence 496
- Health Informatics 18
- Management Science and Operations Research 142
- Information Systems 190
- Computer Vision and Pattern Recognition 99
Countries citing papers authored by Jay Pujara
This map shows the geographic impact of Jay Pujara'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 Jay Pujara with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jay Pujara more than expected).
Fields of papers citing papers by Jay Pujara
This network shows the impact of papers produced by Jay Pujara. 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 Jay Pujara. The network helps show where Jay Pujara may publish in the future.
Co-authors
The 25 scholars most cited alongside Jay Pujara, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 68 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 102 | |
| 2 | 2017 | 63 | |
| 3 | 2017 | 51 | |
| 4 | 2022 | 48 | |
| 5 | 2022 | 36 | |
| 6 | 2020 | 30 | |
| 7 | 2017 | 22 | |
| 8 | 2019 | 21 | |
| 9 | 2021 | 19 | |
| 10 | 2021 | 17 | |
| 11 | 2013 | 17 | |
| 12 | 2021 | 15 | |
| 13 | 2011 | 15 | |
| 14 | Social Group Modeling with Probabilistic Soft Logic | 2012 | 15 |
| 15 | 2018 | 14 | |
| 16 | 2021 | 14 | |
| 17 | 2023 | 14 | |
| 18 | 2017 | 13 | |
| 19 | 2022 | 12 | |
| 20 | 2019 | 11 |
About Jay Pujara
Jay Pujara is a scholar working on Artificial Intelligence, Management Science and Operations Research, Information Systems, Computer Vision and Pattern Recognition and Mechanical Engineering, having authored 68 papers that have together received 738 indexed citations. Recurring topics across this work include Topic Modeling (26 papers), Natural Language Processing Techniques (15 papers), Data Quality and Management (14 papers), Advanced Graph Neural Networks (10 papers), Semantic Web and Ontologies (9 papers), Speech and dialogue systems (5 papers), Data Stream Mining Techniques (5 papers) and Data Mining Algorithms and Applications (4 papers). The work is most often cited by research in Artificial Intelligence (496 citations), Health Informatics (18 citations), Management Science and Operations Research (142 citations), Information Systems (190 citations) and Computer Vision and Pattern Recognition (99 citations). Jay Pujara has collaborated with scholars based in United States, India and Germany. Frequent co-authors include Lise Getoor, Pigi Kouki, John O’Donovan, James Schaffer, Xiang Ren, Fred Morstatter, Pedro Szekely, Dong‐Ho Lee, Pei Zhou and Kristina Lerman. Their work appears in journals such as Knowledge and Information Systems, AI Magazine, Proceedings of the National Academy of Sciences, ACM Transactions on Interactive Intelligent Systems and IEEE Transactions on Wireless Communications.
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.