Behrooz Masoumi

576 citations
44 papers · 386 · h-index 11

Impact in

Papers in

Behrooz Masoumi

42 papers receiving 370 citations

Peers

Behrooz Masoumi
Comparison fields: 5 of 97
  • Artificial Intelligence 159
  • Computer Vision and Pattern Recognition 86
  • Computer Networks and Communications 82
  • Health Information Management 11
  • Information Systems 53
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Citations per year

Countries citing papers authored by Behrooz Masoumi

Since Specialization
Citations

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

Fields of papers citing papers by Behrooz Masoumi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 12 scholars most cited alongside Behrooz Masoumi, 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 Behrooz Masoumi Line = papers co-authored together Behrooz Masoumi 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 202277
2 202159
3 201430
4 202027
5 202026
6 201016
7 201913
8 201711
9 201411
10 202010
11 201010
12 202110
13 20218
14 20207
15 20205
16 20185
17
A Honey Bee Algorithm To Solve Quadratic Assignment Problem
20114
18 20204
19 20224
20 20243

About Behrooz Masoumi

Behrooz Masoumi is a scholar working on Artificial Intelligence, Computer Networks and Communications, Computer Vision and Pattern Recognition, Information Systems and Statistical and Nonlinear Physics, having authored 44 papers that have together received 386 indexed citations. Recurring topics across this work include Optimization and Search Problems (9 papers), Metaheuristic Optimization Algorithms Research (8 papers), Reinforcement Learning in Robotics (7 papers), Complex Network Analysis Techniques (6 papers), IoT and Edge/Fog Computing (5 papers), Opinion Dynamics and Social Influence (5 papers), Game Theory and Applications (3 papers) and Mental Health Research Topics (3 papers). The work is most often cited by research in Artificial Intelligence (159 citations), Computer Vision and Pattern Recognition (86 citations), Computer Networks and Communications (82 citations), Health Information Management (11 citations) and Information Systems (53 citations). Behrooz Masoumi has collaborated with scholars based in Iran. Frequent co-authors include Mohammad Reza Keyvanpour, Babak Karasfi, Mohammad Reza Meybodi, Mohammad Bagher Menhaj, Eslam Nazemi, Saleh Yousefi, Karim Faez, Seyyed Mohsen Hashemi, M. R. Meybodi and Hamidreza Bakhshi. Their work appears in journals such as Journal of Ambient Intelligence and Humanized Computing, Computational Intelligence and Neuroscience, Chaos An Interdisciplinary Journal of Nonlinear Science, Expert Systems with Applications and Reliability Engineering & System Safety.

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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