Poorvi L. Vora

27 papers receiving 296 citations

Peers

Poorvi L. Vora
Comparison fields: 5 of 60
  • Artificial Intelligence 157
  • Computer Vision and Pattern Recognition 154
  • Atomic and Molecular Physics, and Optics 119
  • Sociology and Political Science 55
  • Information Systems 43
Replace Dongyang Wang with:
Dongyang Wang China
Gaofeng Luo China
Subhashini Ganapathy United States
Christian Keimel Germany
Soomin Kim South Korea
Markus Bayer Germany
Julian Habigt Germany
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Sanjoy Mahajan United States
Poorvi L. Vora relative to Dongyang Wang China Dongyang Wang's profile →
Citations per field
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Citations per year

Countries citing papers authored by Poorvi L. Vora

Since Specialization
Citations

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

Fields of papers citing papers by Poorvi L. Vora

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Poorvi L. Vora. 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 Poorvi L. Vora. The network helps show where Poorvi L. Vora may publish in the future.

Co-authorship network of co-authors of Poorvi L. Vora

This figure shows the co-authorship network connecting the top 25 collaborators of Poorvi L. Vora. A scholar is included among the top collaborators of Poorvi L. Vora 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 Poorvi L. Vora. Poorvi L. Vora 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
#WorkIndexed citations
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Minerva– An Efficient {Risk-Limiting} Ballot Polling Audit
1
3 2
4
Scantegrity Responds to Rice Study on Usability of the Scantegrity II Voting System
0
5 3
6
Performance requirements for end-to-end verifiable elections
8
7 2
8 3
9 5
10 3
11 109
12 3
13 17
14 14
15 6
16
Image Capture: Modelling and Calibration of Sensor Responses and their Synthesis from Multispectral Images
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17 2
18 90
19 13
20 1

About Poorvi L. Vora

Poorvi L. Vora is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Marketing, having authored 28 papers that have together received 339 indexed citations. Recurring topics across this work include Internet Traffic Analysis and Secure E-voting (11 papers), Color Science and Applications (6 papers) and Chaos-based Image/Signal Encryption (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (154 citations), Artificial Intelligence (157 citations) and Atomic and Molecular Physics, and Optics (119 citations). Poorvi L. Vora has collaborated with scholars based in United States, Canada and Ireland. Frequent co-authors include H.J. Trussell, Stefan Popoveniuc, David Chaum, Richard Carback, Alan T. Sherman, Jeremy Clark, Nasir Memon, Joyce Farrell, David H. Brainard and Jerome D. Tietz. Their work appears in journals such as Journal of the Optical Society of America A, IEEE Transactions on Information Forensics and Security and Mathematical and Computer Modelling.

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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