Sumit Sharma

502 citations
37 papers · 397 · h-index 11

Impact in

  • Software top 10%
    • Software Reliability and Analysis Research
    • Software Engineering Research
    • Blockchain Technology Applications and Security
    • Software Engineering Techniques and Practices

Papers in

Sumit Sharma

33 papers receiving 381 citations

Peers

Sumit Sharma
Comparison fields: 5 of 72
  • Software 67
  • Information Systems 223
  • Computer Networks and Communications 142
  • Signal Processing 57
  • Health Information Management 18
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Saurabh Bilgaiyan India
A. Shanthini India
Arti Arya India
Yahya Tashtoush Jordan
Vandana Bhattacharjee India
Jianglin Huang Hong Kong
Rashi Kohli India
Asad Abbas South Korea
Dongfang Li China
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Citations per field
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Citations per year

Countries citing papers authored by Sumit Sharma

Since Specialization
Citations

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

Fields of papers citing papers by Sumit Sharma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 17 scholars most cited alongside Sumit 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 Sumit Sharma Line = papers co-authored together Sumit Sharma links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202086
2 202069
3 201554
4 201528
5 201423
6 201520
7 201517
8 201513
9
A Review on Dimension Reduction Techniques in Data Mining
201812
10 201412
11 201811
12 201510
13 20244
14
Revealing New Concepts in Cryptography & Clouds
20124
15
A Survey of Email Spam Filtering Methods
20184
16 20204
17 20153
18 20183
19 20213
20 20183

About Sumit Sharma

Sumit Sharma is a scholar working on Information Systems, Artificial Intelligence, Software, Computer Networks and Communications and Signal Processing, having authored 37 papers that have together received 397 indexed citations. Recurring topics across this work include Software Engineering Research (9 papers), Software Testing and Debugging Techniques (8 papers), Advanced Malware Detection Techniques (7 papers), Software Reliability and Analysis Research (7 papers), Topic Modeling (4 papers), Traffic Prediction and Management Techniques (4 papers), Software System Performance and Reliability (4 papers) and Network Security and Intrusion Detection (3 papers). The work is most often cited by research in Software (67 citations), Information Systems (223 citations), Computer Networks and Communications (142 citations), Signal Processing (57 citations) and Health Information Management (18 citations). Sumit Sharma has collaborated with scholars based in India, United Kingdom and United States. Frequent co-authors include Gagangeet Singh Aujla, Neeraj Kumar, Gitika Sharma, Rasmeet Singh Bali, Swadha Gupta, Kim‐Kwang Raymond Choo, Maninderpal Singh, Amritpal Singh, Gurpreet Kaur and Diksha Diksha. Their work appears in journals such as Indian Journal of Science and Technology, Internet of things, Neural Computing and Applications, IEEE Transactions on Vehicular Technology and Cluster Computing.

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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