Mayank Sharma

1.0k citations
77 papers · 506 · h-index 11

Impact in

Papers in

    • Imbalanced Data Classification Techniques 7
    • Machine Learning and ELM 5
    • Data Stream Mining Techniques 5
    • Software Engineering Research 11
    • Cloud Computing and Resource Management 5

Mayank Sharma

67 papers receiving 479 citations

Peers

Mayank Sharma
Comparison fields: 5 of 108
  • Software 44
  • Health Informatics 14
  • Health Information Management 34
  • Artificial Intelligence 178
  • Signal Processing 57
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Domingo Ortíz-Boyer Spain
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Shilpa Rani India
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Tomáš Horváth Slovakia
Mohammed Ali Saudi Arabia
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Citations per field
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Citations per year

Countries citing papers authored by Mayank Sharma

Since Specialization
Citations

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

Fields of papers citing papers by Mayank Sharma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Mayank Sharma, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Mayank Sharma Line = papers co-authored together Mayank Sharma links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 77 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201383
2 202448
3 201744
4 202244
5 202235
6 201922
7 202317
8 201812
9 202212
10 201811
11 201911
12 201710
13 201710
14 20178
15 20188
16 20208
17 20177
18 20207
19 20186
20 20185

About Mayank Sharma

Mayank Sharma is a scholar working on Artificial Intelligence, Information Systems, Computer Networks and Communications, Computer Vision and Pattern Recognition and Signal Processing, having authored 77 papers that have together received 506 indexed citations. Recurring topics across this work include Software Engineering Research (11 papers), Software Reliability and Analysis Research (9 papers), Imbalanced Data Classification Techniques (7 papers), Face and Expression Recognition (5 papers), Cloud Computing and Resource Management (5 papers), Machine Learning and ELM (5 papers), Data Stream Mining Techniques (5 papers) and Data Management and Algorithms (4 papers). The work is most often cited by research in Software (44 citations), Health Informatics (14 citations), Health Information Management (34 citations), Artificial Intelligence (178 citations) and Signal Processing (57 citations). Mayank Sharma has collaborated with scholars based in India, United States and United Arab Emirates. Frequent co-authors include Nishchal K. Verma, Vishal K. Gupta, Rahul K. Sevakula, Sunil Kumar Khatri, Sumit Soman, Jayadeva, Himanshu Pant, Pooja Sharma, Najam W. Zaidi and Alastair F. Donaldson. Their work appears in journals such as Neurocomputing, IEEE Transactions on Systems Man and Cybernetics Systems, Food Security, Information Sciences and Cell Biochemistry and Function.

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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