Shahriar Badsha

1.7k citations
34 papers · 1.0k indexed · 1 hit paper · h-index 18
Topics
Blockchain Technology Applications and Security (18 papers)Privacy-Preserving Technologies in Data (14 papers)Vehicular Ad Hoc Networks (VANETs) (8 papers)

In The Last Decade

Shahriar Badsha

32 papers receiving 977 citations

Hit Papers

Cybersecurity data science: an overview from machine lear...20202026202220242020100200300

Peers

Shahriar Badsha
Comparison fields: 5 of 93
  • Information Systems 521
  • Computer Networks and Communications 483
  • Artificial Intelligence 384
  • Electrical and Electronic Engineering 235
  • Signal Processing 194
Replace Nawab Muhammad Faseeh Qureshi with:
Nawab Muhammad Faseeh Qureshi South Korea
Geetanjali Rathee India
Jiale Zhang China
Yongrui Qin United Kingdom
Ladjel Bellatreche France
Pushpita Chatterjee United States
Shingo Yamaguchi Japan
Gulshan Kumar India
Stavros Shiaeles United Kingdom
Shahriar Badsha relative to Nawab Muhammad Faseeh Qureshi South Korea Nawab Muhammad Faseeh Qureshi's profile →
Citations per field
00.5×1.5×2.1×
Nawab Muhammad Faseeh Qureshi · 1×
Citations per year

Countries citing papers authored by Shahriar Badsha

Since Specialization
Citations

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

Fields of papers citing papers by Shahriar Badsha

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shahriar Badsha

This figure shows the co-authorship network connecting the top 25 collaborators of Shahriar Badsha. A scholar is included among the top collaborators of Shahriar Badsha 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 Shahriar Badsha. Shahriar Badsha 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
1 4
2 0
3 3
4 9
5 0
6 30
7 23
8 17
9 25
10 25
11 5
12
Cybersecurity data science: an overview from machine learning perspectivebreakdown →
366
13 14
14 86
15 12
16 4
17 12
18 24
19 20
20 25

About Shahriar Badsha

Shahriar Badsha is a scholar working on Information Systems, Artificial Intelligence and Computer Networks and Communications, having authored 34 papers that have together received 1.0k indexed citations. Recurring topics across this work include Blockchain Technology Applications and Security (18 papers), Privacy-Preserving Technologies in Data (14 papers) and Vehicular Ad Hoc Networks (VANETs) (8 papers). The work is most often cited by research in Information Systems (521 citations), Computer Networks and Communications (483 citations) and Signal Processing (194 citations). Shahriar Badsha has collaborated with scholars based in United States, Australia and Saudi Arabia. Frequent co-authors include Shamik Sengupta, A. S. M. Kayes, Alex Ng, Paul Watters, Iqbal H. Sarker, Ibrahim Khalil, Hamed Alqahtani, Mohammed Atiquzzaman, Iman Vakilinia and Hung Manh La. Their work appears in journals such as IEEE Access, Sensors and Information Sciences.

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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