Muhammad Jawad Khan

2.7k total citations
85 papers, 2.0k citations indexed

About

Muhammad Jawad Khan is a scholar working on Cognitive Neuroscience, Biomedical Engineering and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Muhammad Jawad Khan has authored 85 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 57 papers in Cognitive Neuroscience, 42 papers in Biomedical Engineering and 23 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Muhammad Jawad Khan's work include EEG and Brain-Computer Interfaces (53 papers), Non-Invasive Vital Sign Monitoring (32 papers) and Optical Imaging and Spectroscopy Techniques (23 papers). Muhammad Jawad Khan is often cited by papers focused on EEG and Brain-Computer Interfaces (53 papers), Non-Invasive Vital Sign Monitoring (32 papers) and Optical Imaging and Spectroscopy Techniques (23 papers). Muhammad Jawad Khan collaborates with scholars based in Pakistan, South Korea and Canada. Muhammad Jawad Khan's co-authors include Keum‐Shik Hong, Melissa Jiyoun Hong, Noman Naseer, Usman Ghafoor, M. Raheel Bhutta, Yasar Ayaz, Yasar Ayaz, Umer Asgher, Rayyan Azam Khan and Riaz Ahmad and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.

In The Last Decade

Muhammad Jawad Khan

80 papers receiving 2.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Muhammad Jawad Khan Pakistan 22 1.4k 800 707 412 223 85 2.0k
Noman Naseer Pakistan 24 2.0k 1.4× 1.5k 1.9× 1.4k 1.9× 479 1.2× 220 1.0× 105 3.1k
Christian Herff Germany 22 1.3k 0.9× 377 0.5× 346 0.5× 252 0.6× 167 0.7× 61 2.0k
Boreom Lee South Korea 29 1.2k 0.8× 568 0.7× 373 0.5× 201 0.5× 105 0.5× 89 2.7k
Sung-Phil Kim South Korea 22 1.5k 1.1× 487 0.6× 130 0.2× 633 1.5× 175 0.8× 146 2.0k
Pornchai Phukpattaranont Thailand 25 1.5k 1.1× 2.2k 2.8× 159 0.2× 645 1.6× 480 2.2× 124 3.1k
Ou Bai United States 28 2.8k 2.0× 692 0.9× 183 0.3× 969 2.4× 379 1.7× 123 3.8k
Olivier Lambercy Switzerland 33 1.0k 0.7× 2.5k 3.1× 228 0.3× 192 0.5× 218 1.0× 165 4.3k
Po‐Lei Lee Taiwan 27 1.3k 0.9× 401 0.5× 96 0.1× 516 1.3× 160 0.7× 97 2.2k
Junhua Li China 23 1.1k 0.8× 289 0.4× 134 0.2× 165 0.4× 168 0.8× 91 1.7k
Hongzhi Qi China 26 1.7k 1.2× 331 0.4× 102 0.1× 696 1.7× 271 1.2× 124 2.0k

Countries citing papers authored by Muhammad Jawad Khan

Since Specialization
Citations

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

Fields of papers citing papers by Muhammad Jawad Khan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Muhammad Jawad Khan

This figure shows the co-authorship network connecting the top 25 collaborators of Muhammad Jawad Khan. A scholar is included among the top collaborators of Muhammad Jawad 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 Muhammad Jawad Khan. Muhammad Jawad Khan 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.
Waris, Asim, et al.. (2025). Optimizing the impact of time domain segmentation techniques on upper limb EMG decoding using multimodal features. PLoS ONE. 20(5). e0322580–e0322580. 1 indexed citations
2.
3.
Khan, Muhammad Jawad, et al.. (2025). Subject based feature selection for hybrid brain computer interface using genetic algorithm and support vector machine. Results in Engineering. 27. 105649–105649. 1 indexed citations
4.
Waris, Asim, et al.. (2025). Gaussian process latent variable models-ANN based method for automatic features selection and dimensionality reduction for control of EMG-driven systems. Frontiers in Artificial Intelligence. 8. 1506042–1506042. 1 indexed citations
5.
Anwar, Hirra, Muhammad Jawad Khan, Muhammad Fayyaz, Ajmal Mian, & Faisal Shafait. (2024). Wheat Rust Disease Segmentation from Ground Imagery. 706–713. 1 indexed citations
6.
Khan, Muhammad Jawad, et al.. (2023). Engagement detection and enhancement for STEM education through computer vision, augmented reality, and haptics. Image and Vision Computing. 136. 104720–104720. 14 indexed citations
7.
Khan, Muhammad Jawad, et al.. (2023). Real-Time Vehicle Lateral Dynamics Estimation Using State Observer and Adaptive Filter. SHILAP Revista de lepidopterología. 27–27.
8.
Ali, Sara, Faisal Mehmood, Muhammad Jawad Khan, et al.. (2020). A Preliminary Study on Effectiveness of a Standardized Multi-Robot Therapy for Improvement in Collaborative Multi-Human Interaction of Children With ASD. IEEE Access. 8. 109466–109474. 12 indexed citations
9.
Nazeer, Hammad, Noman Naseer, Rayyan Azam Khan, et al.. (2020). Enhancing classification accuracy of fNIRS-BCI using features acquired from vector-based phase analysis. Journal of Neural Engineering. 17(5). 56025–56025. 49 indexed citations
10.
Shahzad, Waseem, Yasar Ayaz, Muhammad Jawad Khan, Noman Naseer, & Amad Zafar. (2020). Characterizing the Effect of Motion Class Taxonomy on the Performance of Hand Motion Classifiers. 58–63. 1 indexed citations
11.
Nazeer, Hammad, Noman Naseer, Muhammad Jawad Khan, et al.. (2020). Enhancing Classification Performance of fNIRS-BCI by Identifying Cortically Active Channels Using the z-Score Method. Sensors. 20(23). 6995–6995. 23 indexed citations
12.
Sajid, Muhammad, et al.. (2020). Prediction of Drag Force on Vehicles in a Platoon Configuration Using Machine Learning. IEEE Access. 8. 201823–201834. 24 indexed citations
13.
Asgher, Umer, et al.. (2019). Assessment and Classification of Mental Workload in the Prefrontal Cortex (PFC) Using Fixed-Value Modified Beer-Lambert Law. IEEE Access. 7. 143250–143262. 26 indexed citations
14.
Hong, Keum‐Shik, Muhammad Jawad Khan, & Melissa Jiyoun Hong. (2018). Feature Extraction and Classification Methods for Hybrid fNIRS-EEG Brain-Computer Interfaces. Frontiers in Human Neuroscience. 12. 246–246. 207 indexed citations
15.
Zafar, Amad, Muhammad Jawad Khan, & Keum‐Shik Hong. (2017). Classification of prefrontal and motor cortex initial dips for fNIRS-based-BCI. 113. 1–6. 1 indexed citations
16.
Zafar, Amad, Keum‐Shik Hong, & Muhammad Jawad Khan. (2016). Initial dip detection based on both HbO and HbR vector-based phase analysis. 5. 543–548. 8 indexed citations
17.
Naseer, Noman, Keum‐Shik Hong, Muhammad Jawad Khan, & M. Raheel Bhutta. (2015). Comparison of artificial neural network and support vector machine classifications for fNIRS-based BCI. 1817–1821. 7 indexed citations
18.
Khan, Muhammad Jawad, Keum‐Shik Hong, Noman Naseer, & M. Raheel Bhutta. (2015). Motor imagery performance evaluation using hybrid EEG-NIRS for BCI. 8. 1150–1155. 6 indexed citations
19.
Khan, Muhammad Jawad & Keum‐Shik Hong. (2015). Active brain area identification using EEG-NIRS signal acquisition. 18. 7–11. 2 indexed citations
20.
Khan, Muhammad Jawad & Keum‐Shik Hong. (2015). Passive BCI based on drowsiness detection: an fNIRS study. Biomedical Optics Express. 6(10). 4063–4063. 159 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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