Ashish Gehani

2.0k citations
72 papers · 821 · h-index 15

Impact in

Papers in

Ashish Gehani

64 papers receiving 774 citations

Peers

Ashish Gehani
Comparison fields: 5 of 47
  • Information Systems and Management 171
  • Signal Processing 239
  • Computer Networks and Communications 435
  • Information Systems 334
  • Software 35
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Wajih Ul Hassan United States
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Citations per field
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Citations per year

Countries citing papers authored by Ashish Gehani

Since Specialization
Citations

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

Fields of papers citing papers by Ashish Gehani

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 72 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201877
2 200065
3 201961
4 201056
5 201852
6 200036
7 201735
8 202135
9 201523
10 199922
11 202122
12
Kernel-supported cost-effective audit logging for causality tracking
201820
13
Towards automated collection of application-level data provenance
201219
14 201019
15 201315
16 200714
17 201114
18
Steps toward managing lineage metadata in grid clusters
200912
19 202411
20 201011

About Ashish Gehani

Ashish Gehani is a scholar working on Computer Networks and Communications, Information Systems and Management, Information Systems, Artificial Intelligence and Signal Processing, having authored 72 papers that have together received 821 indexed citations. Recurring topics across this work include Scientific Computing and Data Management (28 papers), Advanced Data Storage Technologies (18 papers), Distributed and Parallel Computing Systems (16 papers), Advanced Malware Detection Techniques (14 papers), Security and Verification in Computing (11 papers), Distributed systems and fault tolerance (9 papers), Research Data Management Practices (9 papers) and Software System Performance and Reliability (8 papers). The work is most often cited by research in Information Systems and Management (171 citations), Signal Processing (239 citations), Computer Networks and Communications (435 citations), Information Systems (334 citations) and Software (35 citations). Ashish Gehani has collaborated with scholars based in United States, Pakistan and France. Frequent co-authors include John H. Reif, Vinod Yegneswaran, Thomas H. LaBean, Fareed Zaffar, Eunjin Jung, Tanu Malik, Gabriela Ciocarlie, Minyoung Kim, Dongyan Xu and Muhammad Abubakar. Their work appears in journals such as Communications of the ACM, Computer Networks, Queue, Biosystems and IEEE Transactions on Information Forensics and Security.

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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