Vaibhav Anu

32 papers receiving 238 citations

Peers

Vaibhav Anu
Comparison fields: 5 of 61
  • Software 71
  • Radiological and Ultrasound Technology 44
  • Information Systems 177
  • Statistics, Probability and Uncertainty 29
  • Signal Processing 37
Replace Yudistira Asnar with:
Yudistira Asnar Indonesia
Sam Supakkul United States
Timothy Kelly United Kingdom
Elizabeth Fong United States
Denis Hatebur Germany
Chengwei Liu China
Cristina Palomares Spain
Giovanni Giachetti Spain
Muddassar Azam Sindhu Pakistan
Md. Asraful Haque India
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Countries citing papers authored by Vaibhav Anu

Since Specialization
Citations

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

Fields of papers citing papers by Vaibhav Anu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 19 scholars most cited alongside Vaibhav Anu, 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 Vaibhav Anu Line = papers co-authored together Vaibhav Anu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 44 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201846
2 202031
3 201821
4 201618
5 201814
6 201610
7 201610
8 20179
9 20227
10 20217
11 20217
12 20217
13 20216
14 20195
15 20215
16 20215
17 20225
18 20185
19 20204
20 20194

About Vaibhav Anu

Vaibhav Anu is a scholar working on Information Systems, Radiological and Ultrasound Technology, Software, Statistics, Probability and Uncertainty and Computer Networks and Communications, having authored 44 papers that have together received 255 indexed citations. Recurring topics across this work include Software Engineering Research (16 papers), Software Engineering Techniques and Practices (13 papers), Software Reliability and Analysis Research (10 papers), Occupational Health and Safety Research (10 papers), Risk and Safety Analysis (8 papers), Human-Automation Interaction and Safety (5 papers), Advanced Malware Detection Techniques (5 papers) and Teaching and Learning Programming (5 papers). The work is most often cited by research in Software (71 citations), Radiological and Ultrasound Technology (44 citations), Information Systems (177 citations), Statistics, Probability and Uncertainty (29 citations) and Signal Processing (37 citations). Vaibhav Anu has collaborated with scholars based in United States, India and Nigeria. Frequent co-authors include Gursimran Walia, Gary Bradshaw, Jeffrey C. Carver, Kazi Zakia Sultana, Aparna S. Varde, Gary L. Bradshaw, Anurag Goswami, Maninder Singh, Olawande Daramola and Bharath K. Samanthula. Their work appears in journals such as Empirical Software Engineering, ACM SIGMOD Record, Information and Software Technology, Information Security Journal A Global Perspective and Journal of Software Evolution and Process.

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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