Ashwin Paranjape

33 total papers · 1.1k total citations
7 papers, 297 citations indexed

About

Ashwin Paranjape is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, Ashwin Paranjape has authored 7 papers receiving a total of 297 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 1 paper in Information Systems and 1 paper in Computer Vision and Pattern Recognition. Recurrent topics in Ashwin Paranjape's work include Topic Modeling (7 papers), Natural Language Processing Techniques (5 papers) and Speech and dialogue systems (3 papers). Ashwin Paranjape is often cited by papers focused on Topic Modeling (7 papers), Natural Language Processing Techniques (5 papers) and Speech and dialogue systems (3 papers). Ashwin Paranjape collaborates with scholars based in United States, India and South Korea. Ashwin Paranjape's co-authors include Percy Liang, Nelson F. Liu, John Hewitt, Michele Bevilacqua, Kevin Lin, Fabio Petroni, Pushpak Bhattacharyya, Devendra Singh Chaplot, Christopher D. Manning and Arun Tejasvi Chaganty and has published in prestigious journals such as Transactions of the Association for Computational Linguistics, Theory and applications of categories and Proceedings of the AAAI Conference on Artificial Intelligence.

In The Last Decade

Ashwin Paranjape

7 papers receiving 277 citations

Hit Papers

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Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Ashwin Paranjape 184 53 36 24 23 7 297
Weitao Ma 213 1.2× 50 0.9× 24 0.7× 21 0.9× 51 2.2× 6 356
Shaochen Zhong 132 0.7× 40 0.8× 22 0.6× 27 1.1× 27 1.2× 5 261
Qingxiu Dong 186 1.0× 35 0.7× 45 1.3× 17 0.7× 10 0.4× 11 266
Ying Sheng 152 0.8× 48 0.9× 50 1.4× 69 2.9× 7 0.3× 6 303
Hanjie Chen 226 1.2× 28 0.5× 28 0.8× 10 0.4× 37 1.6× 10 320
Isabelle Moulinier 242 1.3× 129 2.4× 22 0.6× 13 0.5× 22 1.0× 11 333
Rob Ashmore 155 0.8× 36 0.7× 32 0.9× 22 0.9× 11 0.5× 9 246
Negar Maleki 135 0.7× 40 0.8× 33 0.9× 14 0.6× 18 0.8× 9 298
Lei Li 195 1.1× 57 1.1× 28 0.8× 46 1.9× 4 0.2× 6 277
Ori Ram 230 1.3× 30 0.6× 71 2.0× 11 0.5× 9 0.4× 7 307

Countries citing papers authored by Ashwin Paranjape

Since Specialization
Citations

This map shows the geographic impact of Ashwin Paranjape'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 Ashwin Paranjape with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ashwin Paranjape more than expected).

Fields of papers citing papers by Ashwin Paranjape

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ashwin Paranjape. 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 Ashwin Paranjape. The network helps show where Ashwin Paranjape may publish in the future.

Co-authorship network of co-authors of Ashwin Paranjape

This figure shows the co-authorship network connecting the top 25 collaborators of Ashwin Paranjape. A scholar is included among the top collaborators of Ashwin Paranjape 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 Ashwin Paranjape. Ashwin Paranjape is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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.

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