Mujtaba Husnain

424 total citations
20 papers, 256 citations indexed

About

Mujtaba Husnain is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Media Technology. According to data from OpenAlex, Mujtaba Husnain has authored 20 papers receiving a total of 256 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 5 papers in Computer Vision and Pattern Recognition and 3 papers in Media Technology. Recurrent topics in Mujtaba Husnain's work include Advanced Text Analysis Techniques (6 papers), Sentiment Analysis and Opinion Mining (4 papers) and Topic Modeling (3 papers). Mujtaba Husnain is often cited by papers focused on Advanced Text Analysis Techniques (6 papers), Sentiment Analysis and Opinion Mining (4 papers) and Topic Modeling (3 papers). Mujtaba Husnain collaborates with scholars based in Pakistan, France and Saudi Arabia. Mujtaba Husnain's co-authors include Malik Muhammad Saad Missen, Shahzad Mumtaz, Mickaël Coustaty, Sikandar Ali, Ali Samad, Muhammad Muzzamil Luqman, Gyu Sang Choi, Jean-Marc Ogier, Salman Qadri and Mukhtaj Khan and has published in prestigious journals such as IEEE Access, Applied Sciences and Computer Methods and Programs in Biomedicine.

In The Last Decade

Mujtaba Husnain

18 papers receiving 245 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mujtaba Husnain Pakistan 9 105 62 45 34 33 20 256
Rekha Bhatia India 6 104 1.0× 54 0.9× 45 1.0× 18 0.5× 54 1.6× 23 244
Md Sah Hj Salam Malaysia 8 112 1.1× 148 2.4× 52 1.2× 34 1.0× 19 0.6× 17 276
Lassaad Ben Ammar Saudi Arabia 8 66 0.6× 45 0.7× 68 1.5× 9 0.3× 28 0.8× 32 273
Sheak Rashed Haider Noori Bangladesh 11 121 1.2× 23 0.4× 47 1.0× 4 0.1× 42 1.3× 46 308
Qin Zhi-guang China 7 69 0.7× 29 0.5× 93 2.1× 11 0.3× 38 1.2× 61 255
Sushovan Chaudhury India 8 89 0.8× 24 0.4× 13 0.3× 10 0.3× 25 0.8× 14 198
Ihtiram Raza Khan India 7 55 0.5× 36 0.6× 85 1.9× 14 0.4× 43 1.3× 46 244
Xin Wei China 8 75 0.7× 89 1.4× 31 0.7× 26 0.8× 6 0.2× 39 222
Hazem Hiary Jordan 11 83 0.8× 163 2.6× 71 1.6× 27 0.8× 14 0.4× 28 359
Dhananjay Bisen India 9 66 0.6× 16 0.3× 50 1.1× 6 0.2× 15 0.5× 26 269

Countries citing papers authored by Mujtaba Husnain

Since Specialization
Citations

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

Fields of papers citing papers by Mujtaba Husnain

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mujtaba Husnain

This figure shows the co-authorship network connecting the top 25 collaborators of Mujtaba Husnain. A scholar is included among the top collaborators of Mujtaba Husnain 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 Mujtaba Husnain. Mujtaba Husnain 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.
Husnain, Mujtaba, et al.. (2025). HybridDLDR: A hybrid deep learning-based drug resistance prediction system of Glioblastoma (GBM) using molecular descriptors and gene expression data. Computer Methods and Programs in Biomedicine. 270. 108913–108913.
2.
Husnain, Mujtaba, et al.. (2025). A drug recommendation system based on response prediction: Integrating gene expression and K-mer fragmentation of drug SMILES using LightGBM. Intelligence-Based Medicine. 11. 100206–100206. 3 indexed citations
3.
Husnain, Mujtaba, et al.. (2024). Drug Efficacy Recommendation System of Glioblastoma (GBM) Using Deep Learning. IEEE Access. 13. 10398–10411. 3 indexed citations
4.
Qadri, Salman, et al.. (2023). Protection-Enhanced Watermarking Scheme Combined With Non-Linear Systems. IEEE Access. 11. 33725–33740. 3 indexed citations
5.
Ali, Sikandar, et al.. (2022). Detection of Deficiency of Nutrients in Grape Leaves Using Deep Network. Mathematical Problems in Engineering. 2022. 1–12. 23 indexed citations
6.
Aamir, Muhammad, et al.. (2022). A Comprehensive Convolutional Neural Network Survey to Detect Glaucoma Disease. Mobile Information Systems. 2022. 1–10. 5 indexed citations
7.
Ali, Sikandar, et al.. (2022). BRScS Approach for Resolving Heterogeneity of Data from Multiple Resources at Semantic Level. Mathematical Problems in Engineering. 2022. 1–13. 1 indexed citations
8.
Ali, Sikandar, et al.. (2022). Voting Classification-Based Diabetes Mellitus Prediction Using Hypertuned Machine-Learning Techniques. Mobile Information Systems. 2022. 1–16. 40 indexed citations
9.
Husnain, Mujtaba, Malik Muhammad Saad Missen, Shahzad Mumtaz, et al.. (2021). Urdu Handwritten Characters Data Visualization and Recognition Using Distributed Stochastic Neighborhood Embedding and Deep Network. Complexity. 2021(1).
10.
Husnain, Mujtaba, et al.. (2021). Event classification from the Urdu language text on social media. PeerJ Computer Science. 7. e775–e775. 4 indexed citations
11.
Missen, Malik Muhammad Saad, et al.. (2021). Multiclass Event Classification from Text. Scientific Programming. 2021. 1–15. 17 indexed citations
12.
Husnain, Mujtaba, Malik Muhammad Saad Missen, Nadeem Akhtar, et al.. (2021). A systematic study on the role of SentiWordNet in opinion mining. Frontiers of Computer Science. 15(4). 10 indexed citations
13.
Husnain, Mujtaba, et al.. (2020). Urdu handwritten text recognition: a survey. IET Image Processing. 14(11). 2291–2300. 14 indexed citations
14.
Missen, Malik Muhammad Saad, Mickaël Coustaty, Gyu Sang Choi, et al.. (2020). Correction: OpinionML—Opinion Markup Language for Sentiment Representation. Symmetry 2019, 11, 545. Symmetry. 12(2). 187–187. 1 indexed citations
15.
Missen, Malik Muhammad Saad, Mickaël Coustaty, Gyu Sang Choi, et al.. (2019). OpinionML—Opinion Markup Language for Sentiment Representation. Symmetry. 11(4). 545–545. 6 indexed citations
16.
Husnain, Mujtaba, Malik Muhammad Saad Missen, Shahzad Mumtaz, et al.. (2019). Visualization of High-Dimensional Data by Pairwise Fusion Matrices Using t-SNE. Symmetry. 11(1). 107–107. 25 indexed citations
17.
Mumtaz, Shahzad, et al.. (2019). An Empirical Approach for Extreme Behavior Identification through Tweets Using Machine Learning. Applied Sciences. 9(18). 3723–3723. 30 indexed citations
18.
Husnain, Mujtaba, Malik Muhammad Saad Missen, Shahzad Mumtaz, et al.. (2019). Recognition of Urdu Handwritten Characters Using Convolutional Neural Network. Applied Sciences. 9(13). 2758–2758. 37 indexed citations
19.
Qadri, Salman, Syed Furqan Qadri, Mujtaba Husnain, et al.. (2019). Machine vision approach for classification of citrus leaves using fused features. International Journal of Food Properties. 22(1). 2072–2089. 33 indexed citations
20.
Asif, Muhammad, et al.. (2016). Hashtag the Tweets: Experimental Evaluation of Semantic Relatedness Measures. International Journal of Advanced Computer Science and Applications. 7(6). 1 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.

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