Jayashree Piri

451 citations
23 papers · 341 · h-index 9

Impact in

Papers in

Jayashree Piri

21 papers receiving 329 citations

Peers

Jayashree Piri
Comparison fields: 5 of 77
  • Health Information Management 30
  • Artificial Intelligence 175
  • Computational Theory and Mathematics 59
  • Computer Vision and Pattern Recognition 54
  • Modeling and Simulation 11
Replace Apeksha Koul with:
Apeksha Koul India
Saleh Ali Alomari Jordan
Wenming He China
Fatma Helmy Ismail Egypt
Murat Canayaz Türkiye
Kareem Kamal A. Ghany Egypt
Mohamed Elaraby Egypt
E. Kannan India
Zuhaira Muhammad Zain Saudi Arabia
Mohammed Amine Chikh Algeria
Jayashree Piri relative to Apeksha Koul India Apeksha Koul's profile →
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Countries citing papers authored by Jayashree Piri

Since Specialization
Citations

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

Fields of papers citing papers by Jayashree Piri

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 18 scholars most cited alongside Jayashree Piri, 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 Jayashree Piri Line = papers co-authored together Jayashree Piri links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202190
2 202275
3 202035
4 201929
5 202126
6 202113
7 202213
8 202312
9 20209
10 20218
11
Quantitative Association Rule Mining using Multi- objective Particle Swarm Optimization
20147
12 20235
13 20224
14 20224
15 20223
16 20232
17 20242
18 20251
19 20241
20 20231

About Jayashree Piri

Jayashree Piri is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Information Systems, Health Information Management and Computer Vision and Pattern Recognition, having authored 23 papers that have together received 341 indexed citations. Recurring topics across this work include Metaheuristic Optimization Algorithms Research (7 papers), Advanced Multi-Objective Optimization Algorithms (4 papers), Evolutionary Algorithms and Applications (3 papers), Handwritten Text Recognition Techniques (3 papers), Machine Learning and ELM (3 papers), Software Engineering Research (2 papers), COVID-19 diagnosis using AI (2 papers) and Artificial Intelligence in Healthcare (2 papers). The work is most often cited by research in Health Information Management (30 citations), Artificial Intelligence (175 citations), Computational Theory and Mathematics (59 citations), Computer Vision and Pattern Recognition (54 citations) and Modeling and Simulation (11 citations). Jayashree Piri has collaborated with scholars based in India, Greece and Malaysia. Frequent co-authors include Puspanjali Mohapatra, Biswaranjan Acharya, Andreas Kanavos, Vassilis C. Gerogiannis, Stella Manika, Farhad Soleimanian Gharehchopogh, Manas Ranjan Pradhan, Rakesh Chandra Balabantaray, Debabrata Singh and Manjit Kaur. Their work appears in journals such as IEEE Access, The Imaging Science Journal, Computers in Biology and Medicine, Mathematics and Algorithms.

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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