Muhammad Iqbal

1.5k total citations · 1 hit paper
52 papers, 955 citations indexed

About

Muhammad Iqbal is a scholar working on Artificial Intelligence, Molecular Biology and Computer Vision and Pattern Recognition. According to data from OpenAlex, Muhammad Iqbal has authored 52 papers receiving a total of 955 indexed citations (citations by other indexed papers that have themselves been cited), including 37 papers in Artificial Intelligence, 16 papers in Molecular Biology and 12 papers in Computer Vision and Pattern Recognition. Recurrent topics in Muhammad Iqbal's work include Evolutionary Algorithms and Applications (28 papers), Metaheuristic Optimization Algorithms Research (25 papers) and Viral Infectious Diseases and Gene Expression in Insects (11 papers). Muhammad Iqbal is often cited by papers focused on Evolutionary Algorithms and Applications (28 papers), Metaheuristic Optimization Algorithms Research (25 papers) and Viral Infectious Diseases and Gene Expression in Insects (11 papers). Muhammad Iqbal collaborates with scholars based in New Zealand, Pakistan and United Arab Emirates. Muhammad Iqbal's co-authors include Will N. Browne, Jun Zhang, Muhammad Irfan, Jiangbin Zheng, Umar Zakir Abdul Hamid, Mengjie Zhang, Bing Xue, Harith Al-Sahaf, Jianxin Li and Khawaja Tehseen Ahmed and has published in prestigious journals such as Expert Systems with Applications, IEEE Access and Pattern Recognition.

In The Last Decade

Muhammad Iqbal

47 papers receiving 910 citations

Hit Papers

DeepShip: An underwater acoustic benchmark dataset and a ... 2021 2026 2022 2024 2021 50 100 150
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. DeepShip: An underwater acoustic benchmark dataset and a separable convolution based autoencoder for classification
    2021 176 citations Muhammad Irfan, Jiangbin Zheng et al. Expert Systems with Applications profile →

Peers

Muhammad Iqbal
Michael Bryant United States
Xueliang Liu China
Jianxin Guo China
Zhipeng Xie China
Yidong Chen China
Stefan Kombrink Czechia
Frédéric Bastien Canada
Edmondo Trentin Italy
Weiran Wang United States
Michael Bryant United States
Muhammad Iqbal
Citations per year, relative to Muhammad Iqbal Muhammad Iqbal (= 1×) peers Michael Bryant

Countries citing papers authored by Muhammad Iqbal

Since Specialization
Citations

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

Fields of papers citing papers by Muhammad Iqbal

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Muhammad Iqbal

This figure shows the co-authorship network connecting the top 25 collaborators of Muhammad Iqbal. A scholar is included among the top collaborators of Muhammad Iqbal 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 Muhammad Iqbal. Muhammad Iqbal 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.
Arshad, Noor Habibah, Talal Ashraf Butt, & Muhammad Iqbal. (2025). A Comprehensive Framework for Intelligent, Scalable, and Performance-Optimized Software Development. IEEE Access. 13. 74062–74077.
3.
Iqbal, Muhammad, et al.. (2024). Prediction of Obesity Categories Based on Physical Activity Using Machine Learning Algorithms. Journal Of Computer Networks Architecture and High Performance Computing. 6(3). 1025–1034. 1 indexed citations
4.
Iqbal, Muhammad, et al.. (2024). A Survey on Learning Classifier Systems from 2022 to 2024. Proceedings of the Genetic and Evolutionary Computation Conference Companion. 1797–1806. 1 indexed citations
5.
Yousaf, Sohail, Muhammad Iqbal, Andrea Buono, Ferdinando Nunziata, & Maurizio Migliaccio. (2024). Active Microwave Sensors for Vegetation Water Content Estimation. CINECA IRIS Institutial research information system (Parthenope University of Naples). 1–6.
6.
Shahid, Muhammad, Muhammad Umair, Muhammad Iqbal, et al.. (2024). Leveraging deep learning for toxic comment detection in cursive languages. PeerJ Computer Science. 10. e2486–e2486. 2 indexed citations
7.
Akram, Sheeraz, et al.. (2023). Deep Learning for Sarcasm Identification in News Headlines. Applied Sciences. 13(9). 5586–5586. 13 indexed citations
8.
9.
Irfan, Muhammad, et al.. (2022). Knowledge extraction and retention based continual learning by using convolutional autoencoder-based learning classifier system. Information Sciences. 591. 287–305. 27 indexed citations
10.
Irfan, Muhammad, et al.. (2021). DeepShip: An underwater acoustic benchmark dataset and a separable convolution based autoencoder for classification. Expert Systems with Applications. 183. 115270–115270. 176 indexed citations breakdown →
11.
Irfan, Muhammad, et al.. (2021). Enhancing learning classifier systems through convolutional autoencoder to classify underwater images. Soft Computing. 25(15). 10423–10440. 18 indexed citations
12.
Iqbal, Muhammad, Harith Al-Sahaf, Bing Xue, & Mengjie Zhang. (2019). Genetic programming with transfer learning for texture image classification. Soft Computing. 23(23). 12859–12871. 8 indexed citations
13.
Iqbal, Muhammad, et al.. (2019). Extracting and reusing blocks of knowledge in learning classifier systems for text classification: a lifelong machine learning approach. Soft Computing. 23(23). 12673–12682. 7 indexed citations
14.
Iqbal, Muhammad, et al.. (2019). Learning Regular Expressions Using XCS-Based Classifier System. International Journal of Pattern Recognition and Artificial Intelligence. 34(10). 2051011–2051011. 1 indexed citations
15.
Li, Jianxin, et al.. (2017). Sentiment analysis and spam detection in short informal text using learning classifier systems. Soft Computing. 22(21). 7281–7291. 61 indexed citations
16.
Ahmed, Khawaja Tehseen, Aun Irtaza, & Muhammad Iqbal. (2017). Fusion of local and global features for effective image extraction. Applied Intelligence. 47(2). 526–543. 33 indexed citations
17.
18.
Hussain, Ayyaz, et al.. (2012). Survey of various feature extraction and classification techniques for facial expression recognition. 138–142. 9 indexed citations
19.
Baig, Abdul Rauf, et al.. (2012). Opposition-Based Discrete PSO Using Natural Encoding for Classification Rule Discovery. International Journal of Advanced Robotic Systems. 9(5). 1 indexed citations
20.
Iqbal, Muhammad, Will N. Browne, & Jun Zhang. (2012). Extracting and using building blocks of knowledge in learning classifier systems. 863–870. 24 indexed citations

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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Michael Bryant Breakdown of academic impact, for papers by Xueliang Liu Breakdown of academic impact, for papers by Jianxin Guo Breakdown of academic impact, for papers by Zhipeng Xie Breakdown of academic impact, for papers by Yidong Chen Breakdown of academic impact, for papers by Stefan Kombrink Breakdown of academic impact, for papers by Frédéric Bastien Breakdown of academic impact, for papers by Edmondo Trentin Breakdown of academic impact, for papers by Weiran Wang
Rankless by CCL
2026