Deepak Arora

43 papers receiving 208 citations

Peers

Deepak Arora
Comparison fields: 5 of 78
  • Signal Processing 45
  • Information Systems 79
  • Software 13
  • Computer Networks and Communications 59
  • Hardware and Architecture 15
Replace Sanja Maravić Čisar with:
Sanja Maravić Čisar Serbia
Yulia Burkatovskaya Russia
Elliott Wen New Zealand
Sarah Mount United Kingdom
Shadi Nashwan Saudi Arabia
Zhenyu Wang China
Christoph Endres Germany
Gaurav Gupta United States
Deepak Arora relative to Sanja Maravić Čisar Serbia Sanja Maravić Čisar's profile →
Citations per field
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Citations per year

Countries citing papers authored by Deepak Arora

Since Specialization
Citations

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

Fields of papers citing papers by Deepak Arora

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Deepak Arora, 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 Deepak Arora Line = papers co-authored together Deepak Arora links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 53 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201522
2 202117
3 202014
4 201814
5 202211
6 202210
7 20239
8
Software Quality Estimation through Object Oriented Design Metrics
20119
9
UML Modeling of a Protocol for Establishing Mutual Exclusion in Distributed Computer System
20089
10 20178
11 20138
12 20188
13
Performance comparison of commercial VMM: ESXI, XEN, HYPER-V & KVM
20168
14 20247
15 20176
16 20226
17 20096
18 20115
19 20205
20 20214

About Deepak Arora

Deepak Arora is a scholar working on Information Systems, Computer Networks and Communications, Signal Processing, Artificial Intelligence and Cognitive Neuroscience, having authored 53 papers that have together received 240 indexed citations. Recurring topics across this work include Advanced Malware Detection Techniques (5 papers), EEG and Brain-Computer Interfaces (5 papers), Blockchain Technology Applications and Security (5 papers), Biometric Identification and Security (4 papers), Anomaly Detection Techniques and Applications (4 papers), Sleep and Work-Related Fatigue (4 papers), IoT-based Smart Home Systems (4 papers) and Distributed and Parallel Computing Systems (4 papers). The work is most often cited by research in Signal Processing (45 citations), Information Systems (79 citations), Software (13 citations), Computer Networks and Communications (59 citations) and Hardware and Architecture (15 citations). Deepak Arora has collaborated with scholars based in India, United Arab Emirates and United States. Frequent co-authors include Vipin Saxena, Puneet Sharma, Sabita Khatri, Anil Kumar, Puneet Sharma, Prateek Singhal, Pawan Singh, Brijesh Kumar Chaurasia, Krishna Kant Agrawal and Rohit Saxena. Their work appears in journals such as Mathematical Methods in the Applied Sciences, IEEE Sensors Journal, Journal of Organizational and End User Computing, Multimedia Tools and Applications and International Journal of Electronic Security and Digital Forensics.

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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