Harshil Shah

796 total citations
23 papers, 456 citations indexed

About

Harshil Shah is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Molecular Biology. According to data from OpenAlex, Harshil Shah has authored 23 papers receiving a total of 456 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Computer Vision and Pattern Recognition, 7 papers in Artificial Intelligence and 3 papers in Molecular Biology. Recurrent topics in Harshil Shah's work include Topic Modeling (4 papers), Natural Language Processing Techniques (3 papers) and Metabolomics and Mass Spectrometry Studies (2 papers). Harshil Shah is often cited by papers focused on Topic Modeling (4 papers), Natural Language Processing Techniques (3 papers) and Metabolomics and Mass Spectrometry Studies (2 papers). Harshil Shah collaborates with scholars based in United States, India and United Kingdom. Harshil Shah's co-authors include Jolene K. Diedrich, John R. Yates, Claire Delahunty, Daniel Cociorva, Tao Xu, Bingwen Lu, Xiaolu Han, Yu Gao, Johannes A. Hewel and Catherine C. L. Wong and has published in prestigious journals such as Bioinformatics, IEEE Computer Graphics and Applications and Journal of Proteomics.

In The Last Decade

Harshil Shah

18 papers receiving 455 citations

Peers

Harshil Shah
Comparison fields: 5 of 104
  • Molecular Biology 295
  • Spectroscopy 65
  • Cell Biology 60
  • Oncology 33
  • Physiology 29
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Sílvia Bronsoms Spain
Luc Canard France
Zhen-Lin Chen China
Sung Kyu Robin Park United States
Cristina Viéitez Germany
Celine Sin Austria
Nicolas Lentze Switzerland
Julia Koehler Leman United States
Tianyun Zhao China
Matija Dreze United States
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Citations per field, relative to Harshil Shah
Harshil Shah · 1×
Citations per year, relative to Harshil Shah
Harshil Shah · 1×

Countries citing papers authored by Harshil Shah

Since Specialization
Citations

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

Fields of papers citing papers by Harshil Shah

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Harshil Shah

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

All Works

20 of 20 papers shown
# Work Indexed citations
1 1
2 0
3 1
4 1
5 2
6 1
7 1
8 2
9 0
10
Generative Neural Machine Translation
10
11 0
12 2
13 9
14 10
15 353
16 4
17 54
18
AIVIES: An Artificially Intelligent Voice Interactive Enquiry System
0
19 0
20 1

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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