Aneesh Krishna

1.4k citations
122 papers · 811 · h-index 14

Impact in

Papers in

    • Service-Oriented Architecture and Web Services 23
    • Software Engineering Research 19
    • Software Engineering Techniques and Practices 15
    • Advanced Software Engineering Methodologies 29
    • Multi-Agent Systems and Negotiation 8

Aneesh Krishna

106 papers receiving 743 citations

Peers

Aneesh Krishna
Comparison fields: 5 of 114
  • Computer Vision and Pattern Recognition 259
  • Software 43
  • Information Systems 204
  • Management Information Systems 59
  • Artificial Intelligence 208
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Luís Iribarne Spain
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Citations per field
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Citations per year

Countries citing papers authored by Aneesh Krishna

Since Specialization
Citations

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

Fields of papers citing papers by Aneesh Krishna

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 122 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2013164
2 201639
3 202236
4 202334
5 201628
6 202027
7 201026
8
A combined approach for supporting the business process model lifecycle
200620
9 201619
10 201518
11 201415
12 201715
13 201613
14 201913
15 201812
16 201212
17 201411
18
Optimal selection of operationalizations for non-functional requirements
201311
19 201211
20 201410

About Aneesh Krishna

Aneesh Krishna is a scholar working on Information Systems, Artificial Intelligence, Management Information Systems, Computer Networks and Communications and Computer Vision and Pattern Recognition, having authored 122 papers that have together received 811 indexed citations. Recurring topics across this work include Advanced Software Engineering Methodologies (29 papers), Service-Oriented Architecture and Web Services (23 papers), Business Process Modeling and Analysis (22 papers), Software Engineering Research (19 papers), Software Engineering Techniques and Practices (15 papers), Face and Expression Recognition (8 papers), Multi-Agent Systems and Negotiation (8 papers) and Advanced Neural Network Applications (7 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (259 citations), Software (43 citations), Information Systems (204 citations), Management Information Systems (59 citations) and Artificial Intelligence (208 citations). Aneesh Krishna has collaborated with scholars based in Australia, India and Norway. Frequent co-authors include Wanquan Liu, Ajmal Mian, Raj P. Gopalan, Duc-Son Pham, Aditya Ghose, Sajib Mistry, Mahbuba Afrin, Arshinder Kaur, Tele Tan and Senjian An. Their work appears in journals such as Journal of the Association for Information Systems, The Computer Journal, Neurocomputing, Disability and Rehabilitation Assistive Technology and Pattern Analysis and Applications.

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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