Madjid Khalilian

828 total citations
28 papers, 543 citations indexed

About

Madjid Khalilian is a scholar working on Artificial Intelligence, Information Systems and Computer Networks and Communications. According to data from OpenAlex, Madjid Khalilian has authored 28 papers receiving a total of 543 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Artificial Intelligence, 7 papers in Information Systems and 4 papers in Computer Networks and Communications. Recurrent topics in Madjid Khalilian's work include Advanced Clustering Algorithms Research (7 papers), Metaheuristic Optimization Algorithms Research (7 papers) and AI in cancer detection (4 papers). Madjid Khalilian is often cited by papers focused on Advanced Clustering Algorithms Research (7 papers), Metaheuristic Optimization Algorithms Research (7 papers) and AI in cancer detection (4 papers). Madjid Khalilian collaborates with scholars based in Iran and Malaysia. Madjid Khalilian's co-authors include Javad Mohammadzadeh, Sasan Harifi, Sadoullah Ebrahimnejad, Norwati Mustapha, Azam Bastanfard, Farsad Zamani Boroujeni, Md. Nasir Sulaiman, Aida Mustapha, Ali Najafi and Ali Mamat and has published in prestigious journals such as Computers in Human Behavior, IEEE Transactions on Fuzzy Systems and Safety Science.

In The Last Decade

Madjid Khalilian

24 papers receiving 513 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Madjid Khalilian Iran 13 262 79 71 67 66 28 543
Shafaatunnur Hasan Malaysia 12 428 1.6× 100 1.3× 70 1.0× 46 0.7× 93 1.4× 38 659
Xu Tan China 19 502 1.9× 134 1.7× 83 1.2× 61 0.9× 74 1.1× 61 915
Jing Xiao China 15 400 1.5× 63 0.8× 91 1.3× 37 0.6× 112 1.7× 41 865
Yubo Zhang China 11 179 0.7× 60 0.8× 37 0.5× 49 0.7× 91 1.4× 24 456
Yan Zhuang Macao 13 288 1.1× 52 0.7× 37 0.5× 85 1.3× 177 2.7× 67 632
Philip S. Thomas United States 14 406 1.5× 36 0.5× 79 1.1× 62 0.9× 56 0.8× 45 790
Autilia Vitiello Italy 18 549 2.1× 90 1.1× 91 1.3× 71 1.1× 195 3.0× 92 887
László Kovács Hungary 10 288 1.1× 72 0.9× 32 0.5× 31 0.5× 219 3.3× 120 654
Jonghun Park South Korea 15 182 0.7× 131 1.7× 62 0.9× 37 0.6× 113 1.7× 68 690
Jiamou Liu New Zealand 13 280 1.1× 96 1.2× 35 0.5× 79 1.2× 203 3.1× 96 692

Countries citing papers authored by Madjid Khalilian

Since Specialization
Citations

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

Fields of papers citing papers by Madjid Khalilian

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Madjid Khalilian

This figure shows the co-authorship network connecting the top 25 collaborators of Madjid Khalilian. A scholar is included among the top collaborators of Madjid Khalilian based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Madjid Khalilian. Madjid Khalilian is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
2.
Khalilian, Madjid, et al.. (2025). Optimized Active Fuzzy Deep Federated Learning for predicting autism spectrum disorder. Network Modeling Analysis in Health Informatics and Bioinformatics. 14(1).
3.
Khalilian, Madjid, et al.. (2024). Optimizing the Hybrid Feature Selection in the DNA Microarray for Cancer Diagnosis Using Fuzzy Entropy and the Giza Pyramid Construction Algorithm. International Journal of Computational Intelligence and Applications. 24(1). 1 indexed citations
4.
Harifi, Sasan, Madjid Khalilian, & Javad Mohammadzadeh. (2023). Swarm based automatic clustering using nature inspired Emperor Penguins Colony algorithm. Evolving Systems. 14(6). 1083–1099. 3 indexed citations
5.
Khalilian, Madjid, et al.. (2021). Automatic breast mass detection in mammograms using density of wavelet coefficients and a patch-based CNN. International Journal of Computer Assisted Radiology and Surgery. 16(10). 1805–1815. 5 indexed citations
6.
Harifi, Sasan, Javad Mohammadzadeh, Madjid Khalilian, & Sadoullah Ebrahimnejad. (2021). Hybrid-EPC: an Emperor Penguins Colony algorithm with crossover and mutation operators and its application in community detection. Progress in Artificial Intelligence. 10(2). 181–193. 14 indexed citations
7.
Khalilian, Madjid, et al.. (2021). An Efficient Method for Automated Breast Mass Segmentation and Classification in Digital Mammograms. Iranian Journal of Radiology. 18(3). 4 indexed citations
8.
Harifi, Sasan, Madjid Khalilian, Javad Mohammadzadeh, & Sadoullah Ebrahimnejad. (2020). New generation of metaheuristics by inspiration from ancient. 256–261. 2 indexed citations
9.
Harifi, Sasan, Javad Mohammadzadeh, Madjid Khalilian, & Sadoullah Ebrahimnejad. (2020). Giza Pyramids Construction: an ancient-inspired metaheuristic algorithm for optimization. Evolutionary Intelligence. 14(4). 1743–1761. 107 indexed citations
10.
Harifi, Sasan, Madjid Khalilian, Javad Mohammadzadeh, & Sadoullah Ebrahimnejad. (2020). Using Metaheuristic Algorithms to Improve k-Means Clustering: A Comparative Study. Revue d intelligence artificielle. 34(3). 297–305. 5 indexed citations
11.
Harifi, Sasan, Madjid Khalilian, Javad Mohammadzadeh, & Sadoullah Ebrahimnejad. (2020). Optimization in solving inventory control problem using nature inspired Emperor Penguins Colony algorithm. Journal of Intelligent Manufacturing. 32(5). 1361–1375. 27 indexed citations
12.
Harifi, Sasan, Madjid Khalilian, Javad Mohammadzadeh, & Sadoullah Ebrahimnejad. (2020). Optimizing a Neuro-Fuzzy System Based on Nature-Inspired Emperor Penguins Colony Optimization Algorithm. IEEE Transactions on Fuzzy Systems. 28(6). 1110–1124. 37 indexed citations
13.
Bastanfard, Azam, et al.. (2019). SNEFL: Social network explicit fuzzy like dataset and its application for Incel detection. Multimedia Tools and Applications. 78(23). 33457–33486. 19 indexed citations
14.
Bastanfard, Azam, et al.. (2019). A personalized gamification method for increasing user engagement in social networks. Social Network Analysis and Mining. 9(1). 34 indexed citations
15.
Khalilian, Madjid, et al.. (2017). Derailment accident risk assessment based on ensemble classification method. Safety Science. 110. 3–10. 29 indexed citations
16.
Khalilian, Madjid, et al.. (2015). Breast mass association rules extraction to detect cancerous masses. 5. 337–341. 2 indexed citations
17.
Khalilian, Madjid, et al.. (2010). A Novel Approach for High Dimensional Data Clustering. 20. 264–267. 13 indexed citations
18.
Khalilian, Madjid, et al.. (2010). A Novel K-Means Based Clustering Algorithm for High Dimensional Data Sets. 9 indexed citations
19.
Khalilian, Madjid, Farsad Zamani Boroujeni, Aida Mustapha, & Md. Nasir Sulaiman. (2009). K-Means Divide and Conquer Clustering. 306–309. 18 indexed citations
20.

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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