Arjun Chandra

955 citations
16 papers · 449 indexed · h-index 9

Impact in

    • Metaheuristic Optimization Algorithms Research
    • Evolutionary Algorithms and Applications
    • Advanced Software Engineering Methodologies
    • Neural Networks and Applications
    • Machine Learning and Data Classification

Papers in

Arjun Chandra

16 papers receiving 437 citations

Peers

Arjun Chandra
Comparison fields: 5 of 84
  • Artificial Intelligence 259
  • Software 19
  • Computer Networks and Communications 107
  • Hardware and Architecture 25
  • Computer Vision and Pattern Recognition 73
Replace Jamil Ahmad with:
Jamil Ahmad Pakistan
Jongho Nang South Korea
Masahito Kurihara Japan
Bhabani Shankar Prasad Mishra India
Mingxing Duan China
Olivier Buffet France
Chiara Piacentini United Kingdom
M. M. Raghuwanshi India
Yuqi Chen China
Haibin Zheng China
Arjun Chandra relative to Jamil Ahmad Pakistan Jamil Ahmad's profile →
Citations per field
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Citations per year

Countries citing papers authored by Arjun Chandra

Since Specialization
Citations

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

Fields of papers citing papers by Arjun Chandra

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 24 scholars most cited alongside Arjun Chandra, 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 Arjun Chandra Line = papers co-authored together Arjun Chandra links everyone, so they are left out of the graph.

All Works

16 of 16 papers shown
#Work
1 2006110
2 2006105
3 201177
4 201537
5 201224
6 201421
7
Evolutionary Framework for the Construction of Diverse Hybrid Ensembles
200520
8 201319
9 201517
10 20235
11 20204
12 20143
13 20133
14 20132
15 20251
16 20221

About Arjun Chandra

Arjun Chandra is a scholar working on Artificial Intelligence, Computer Networks and Communications, Biomedical Engineering, Surgery and Computational Theory and Mathematics, having authored 16 papers that have together received 449 indexed citations. Recurring topics across this work include Evolutionary Algorithms and Applications (3 papers), Metaheuristic Optimization Algorithms Research (3 papers), Neural Networks and Reservoir Computing (2 papers), Nonlinear Dynamics and Pattern Formation (2 papers), Auction Theory and Applications (2 papers), Slime Mold and Myxomycetes Research (2 papers), Game Theory and Applications (2 papers) and Advanced Multi-Objective Optimization Algorithms (2 papers). The work is most often cited by research in Artificial Intelligence (259 citations), Software (19 citations), Computer Networks and Communications (107 citations), Hardware and Architecture (25 citations) and Computer Vision and Pattern Recognition (73 citations). Arjun Chandra has collaborated with scholars based in United Kingdom, Norway and Austria. Frequent co-authors include Xin Yao, Peter R. Lewis, Jim Tørresen, Rami Bahsoon, Kyrre Glette, Lukas Esterle, S. Parsons, Bernhard Rinner, Tao Chen and Kristof Van Moffaert. Their work appears in journals such as Computer, Journal of Orthopaedic Trauma, Neurocomputing, Wear and Bone & Joint Open.

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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