Varun Gangal

612 citations
10 papers · 92 indexed · h-index 6
Topics
Topic Modeling (7 papers)Natural Language Processing Techniques (7 papers)Speech and dialogue systems (2 papers)
Journals
IRIS Research product catalog (Sapienza University of Rome)Proceedings of the 2021 Conference on Empirical Methods in Natural Language ProcessingProceedings of the AAAI Conference on Artificial Intelligence
Partner nations
United StatesItalyIndia

In The Last Decade

Varun Gangal

9 papers receiving 89 citations

Peers

Varun Gangal
Comparison fields: 5 of 24
  • Artificial Intelligence 80
  • Computer Vision and Pattern Recognition 23
  • Information Systems 11
  • Economics and Econometrics 6
  • Communication 4
Replace Harsh Jhamtani with:
Harsh Jhamtani United States
Onur Çelebi Burundi
David Ifeoluwa Adelani Germany
Marius Mosbach Germany
Giannis Karamanolakis United States
Linyong Nan United States
Prajjwal Bhargava United States
Elvys Linhares Pontes France
Thomas Scialom France
Anwen Hu China
Varun Gangal relative to Harsh Jhamtani United States Harsh Jhamtani's profile →
Citations per field
00.5×2.7×
Harsh Jhamtani · 1×
Citations per year

Countries citing papers authored by Varun Gangal

Since Specialization
Citations

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

Fields of papers citing papers by Varun Gangal

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Varun Gangal

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

All Works

10 of 10 papers shown
#WorkIndexed citations
1 0
2 1
3 3
4 11
5 10
6 14
7 28
8 7
9 16
10 2

About Varun Gangal

Varun Gangal is a scholar working on Artificial Intelligence, General Social Sciences and Biophysics, having authored 10 papers that have together received 92 indexed citations. Recurring topics across this work include Topic Modeling (7 papers), Natural Language Processing Techniques (7 papers) and Speech and dialogue systems (2 papers). The work is most often cited by research in Artificial Intelligence (80 citations), Computer Vision and Pattern Recognition (23 citations) and General Social Sciences (2 citations). Varun Gangal has collaborated with scholars based in United States, Italy and India. Frequent co-authors include Eduard Hovy, Sonal Gupta, Arash Einolghozati, Harsh Jhamtani, Taylor Berg-Kirkpatrick, Jingbo Shang, Graham Neubig, Teruko Mitamura, Malihe Alikhani and Dongyeop Kang. Their work appears in journals such as IRIS Research product catalog (Sapienza University of Rome), Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing and Proceedings of the AAAI Conference on Artificial Intelligence.

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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