Zardad Khan

846 total citations
39 papers, 525 citations indexed

About

Zardad Khan is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Molecular Biology. According to data from OpenAlex, Zardad Khan has authored 39 papers receiving a total of 525 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Artificial Intelligence, 12 papers in Computer Vision and Pattern Recognition and 11 papers in Molecular Biology. Recurrent topics in Zardad Khan's work include Face and Expression Recognition (12 papers), Gene expression and cancer classification (11 papers) and Machine Learning and Data Classification (7 papers). Zardad Khan is often cited by papers focused on Face and Expression Recognition (12 papers), Gene expression and cancer classification (11 papers) and Machine Learning and Data Classification (7 papers). Zardad Khan collaborates with scholars based in Pakistan, United Arab Emirates and United Kingdom. Zardad Khan's co-authors include Dost Muhammad Khan, Berthold Lausen, Aris Perperoglou, Osama Mahmoud, Werner Adler, Amjad Ali, Asma Gul, Miftahuddin Miftahuddin, Umair Khalil and Muhammad Aamir and has published in prestigious journals such as PLoS ONE, Scientific Reports and Expert Systems with Applications.

In The Last Decade

Zardad Khan

33 papers receiving 503 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Zardad Khan Pakistan	13	183	102	85	66	43	39	525
Santi Wulan Purnami Indonesia	10	156 0.9×	107 1.0×	35 0.4×	37 0.6×	15 0.3×	80	447
Aqib Ali Pakistan	10	100 0.5×	39 0.4×	20 0.2×	47 0.7×	16 0.4×	33	492
Alireza Farhangfar Canada	6	276 1.5×	75 0.7×	27 0.3×	75 1.1×	47 1.1×	8	478
Max G’Sell United States	8	214 1.2×	29 0.3×	64 0.8×	200 3.0×	35 0.8×	13	570
Devvi Sarwinda Indonesia	14	330 1.8×	227 2.2×	79 0.9×	14 0.2×	10 0.2×	80	854
Ignacio Molina United States	7	199 1.1×	51 0.5×	34 0.4×	64 1.0×	28 0.7×	15	467
Vadim Borisov Russia	9	223 1.2×	55 0.5×	42 0.5×	5 0.1×	28 0.7×	48	652
Harshvardhan GM India	11	162 0.9×	96 0.9×	33 0.4×	8 0.1×	16 0.4×	20	488
Chiao-Wen Liu Taiwan	10	247 1.3×	62 0.6×	26 0.3×	13 0.2×	35 0.8×	12	486

Countries citing papers authored by Zardad Khan

Since Specialization

Citations

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

Fields of papers citing papers by Zardad Khan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zardad Khan

This figure shows the co-authorship network connecting the top 25 collaborators of Zardad Khan. A scholar is included among the top collaborators of Zardad Khan 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 Zardad Khan. Zardad Khan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Jan, Salman, et al.. (2025). FS-SVM: A Synergistic Approach to High-Dimensional Feature Selection. IEEE Access. 13. 147593–147603.

Khan, Zardad, et al.. (2025). Customer Lifetime Value Modeling via Two Stage Selected Trees Ensembles. IEEE Access. 13. 115236–115247.

Ali, Amjad, et al.. (2025). Optimized feature selection in high-dimensional gene expression data using weighted differential gene expression analysis. Applied Soft Computing. 180. 113329–113329. 1 indexed citations

Khan, Dost Muhammad, et al.. (2025). Margin weighted robust discriminant score for feature selection in imbalanced gene expression classification. PLoS ONE. 20(6). e0325147–e0325147.

Ali, Amjad, et al.. (2024). An Optimal Random Projection k Nearest Neighbors Ensemble via Extended Neighborhood Rule for Binary Classification. IEEE Access. 12. 61401–61409. 6 indexed citations

Khan, Zardad, et al.. (2024). Regularized ensemble learning for prediction and risk factors assessment of students at risk in the post-COVID era. Scientific Reports. 14(1). 16200–16200. 3 indexed citations

Khan, Dost Muhammad, et al.. (2023). A New Generalized Logarithmic–X Family of Distributions with Biomedical Data Analysis. Applied Sciences. 13(6). 3668–3668. 15 indexed citations

Ali, Amjad, et al.. (2023). Feature selection for high dimensional microarray gene expression data via weighted signal to noise ratio. PLoS ONE. 18(4). e0284619–e0284619. 9 indexed citations

Khan, Zardad, et al.. (2022). Gene Selection in Binary Classification Problems Within Functional Genomics Experiments via Robust Fisher Score. IEEE Access. 10. 51682–51692. 12 indexed citations

10.

Ali, Amjad, Dost Muhammad Khan, Zardad Khan, et al.. (2022). A New Member of T‐X Family with Applications in Different Sectors. Journal of Mathematics. 2022(1). 9 indexed citations

11.

Ali, Amjad, et al.. (2022). Optimal Causal Decision Trees Ensemble for Improved Prediction and Causal Inference. IEEE Access. 10. 13000–13011. 11 indexed citations

12.

Aamir, Muhammad, et al.. (2022). Forecasting crude oil prices volatility by reconstructing EEMD components using ARIMA and FFNN models. Frontiers in Energy Research. 10. 5 indexed citations

13.

Rehman, Atiq Ur, et al.. (2022). Model Selection Using K-Means Clustering Algorithm for the Symmetrical Segmentation of Remote Sensing Datasets. Symmetry. 14(6). 1149–1149. 28 indexed citations

14.

Naeem, Muhammad, et al.. (2021). Comparative analysis of machine learning approaches to analyze and predict the COVID-19 outbreak. PeerJ Computer Science. 7. e746–e746. 23 indexed citations

15.

Gefeller, Olaf, Asma Gul, Folkert K. Horn, et al.. (2016). Ensemble Pruning for Glaucoma Detection in an Unbalanced Data Set. Methods of Information in Medicine. 55(6). 557–563. 7 indexed citations

16.

Khan, Zardad, Asma Gul, Aris Perperoglou, et al.. (2016). An Ensemble of Optimal Trees for Classification and Regression (OTE). Open Access at Essex (University of Essex). 1 indexed citations

17.

Gul, Asma, Aris Perperoglou, Zardad Khan, et al.. (2016). Ensemble of a subset of kNN classifiers. Advances in Data Analysis and Classification. 12(4). 827–840. 77 indexed citations

18.

Khalil, Umair, et al.. (2016). Unit Root Testing and Estimation in Nonlinear ESTAR Models with Normal and Non-Normal Errors. PLoS ONE. 11(11). e0166990–e0166990. 2 indexed citations

19.

Mahmoud, Osama, Andrew Harrison, Aris Perperoglou, et al.. (2014). A feature selection method for classification within functional genomics experiments based on the proportional overlapping score. BMC Bioinformatics. 15(1). 274–274. 32 indexed citations

20.

Khan, Zardad, Javid Shabbir, Martin Griffiths, & Berthold Lausen. (2013). On the ratio method of estimation via auxiliary attributes in simple and stratified random sampling. Open Access at Essex (University of Essex). 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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