Vasu Sharma

95 total papers · 1.3k total citations
20 papers, 95 citations indexed

About

Vasu Sharma is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computer Networks and Communications. According to data from OpenAlex, Vasu Sharma has authored 20 papers receiving a total of 95 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Artificial Intelligence, 7 papers in Computer Vision and Pattern Recognition and 4 papers in Computer Networks and Communications. Recurrent topics in Vasu Sharma's work include Natural Language Processing Techniques (4 papers), Multimodal Machine Learning Applications (4 papers) and Topic Modeling (3 papers). Vasu Sharma is often cited by papers focused on Natural Language Processing Techniques (4 papers), Multimodal Machine Learning Applications (4 papers) and Topic Modeling (3 papers). Vasu Sharma collaborates with scholars based in India, United States and Germany. Vasu Sharma's co-authors include Kolin Paul, Rohan Paul, Nishant Agrawal, S. Balakrishnan, Akshay Kumar, Louis–Philippe Morency, Mahmoud Al Ismail, Teruko Mitamura, Eric Nyberg and Ankit Shah and has published in prestigious journals such as Cancer Research and 2019 3rd International conference on Electronics, Communication and Aerospace Technology (ICECA).

In The Last Decade

Vasu Sharma

18 papers receiving 86 citations

Author Peers

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

Author Last Decade Papers Cites
Vasu Sharma 31 25 22 19 12 20 95
Krzysztof Kutt 20 0.6× 28 1.1× 21 1.0× 16 0.8× 12 1.0× 15 114
Nathaniel Blanchard 51 1.6× 30 1.2× 34 1.5× 12 0.6× 19 1.6× 21 180
Assaf B. Spanier 20 0.6× 55 2.2× 26 1.2× 27 1.4× 6 0.5× 13 155
Nuno Almeida 56 1.8× 12 0.5× 41 1.9× 44 2.3× 7 0.6× 29 224
Paraskevi Theodorou 23 0.7× 52 2.1× 8 0.4× 22 1.2× 41 3.4× 19 237
Michael Schmitz 46 1.5× 20 0.8× 15 0.7× 39 2.1× 13 1.1× 22 142
Robert M. Schumacher 46 1.5× 13 0.5× 7 0.3× 42 2.2× 12 1.0× 20 150
Nadine Ravinet 31 1.0× 50 2.0× 24 1.1× 39 2.1× 19 1.6× 17 231
Deborah Förster 37 1.2× 52 2.1× 30 1.4× 26 1.4× 8 0.7× 19 219
Audrey Serna 24 0.8× 13 0.5× 43 2.0× 38 2.0× 35 2.9× 18 217

Countries citing papers authored by Vasu Sharma

Since Specialization
Citations

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

Fields of papers citing papers by Vasu Sharma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Vasu Sharma

This figure shows the co-authorship network connecting the top 25 collaborators of Vasu Sharma. A scholar is included among the top collaborators of Vasu Sharma 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 Vasu Sharma. Vasu Sharma 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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