Aimal Khan

915 total citations
42 papers, 682 citations indexed

About

Aimal Khan is a scholar working on Electrical and Electronic Engineering, Computer Networks and Communications and Artificial Intelligence. According to data from OpenAlex, Aimal Khan has authored 42 papers receiving a total of 682 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Electrical and Electronic Engineering, 18 papers in Computer Networks and Communications and 10 papers in Artificial Intelligence. Recurrent topics in Aimal Khan's work include Cooperative Communication and Network Coding (8 papers), Software-Defined Networks and 5G (7 papers) and Full-Duplex Wireless Communications (7 papers). Aimal Khan is often cited by papers focused on Cooperative Communication and Network Coding (8 papers), Software-Defined Networks and 5G (7 papers) and Full-Duplex Wireless Communications (7 papers). Aimal Khan collaborates with scholars based in Pakistan, Germany and Canada. Aimal Khan's co-authors include Nashid Shahriar, Reaz Ahmed, Raouf Boutaba, Robert Broadwater, Milad Ghaznavi, Khalid Alsubhi, Jeebak Mitra, Shihabur Rahman Chowdhury, Ayaz Ahmad and Muhammad Attique Khan and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Access and IEEE Journal on Selected Areas in Communications.

In The Last Decade

Aimal Khan

40 papers receiving 650 citations

Peers

Aimal Khan
Sudhir K. Routray India
Muhammad Abubakar Pakistan
Amjad Alsirhani Saudi Arabia
Davide Adami Italy
Travis Atkison United States
Tetsuya Oda Japan
Lakshmi Boppana India
Marwa Sharawi Egypt
Shiwei Gao China
Sudhir K. Routray India
Aimal Khan
Citations per year, relative to Aimal Khan Aimal Khan (= 1×) peers Sudhir K. Routray

Countries citing papers authored by Aimal Khan

Since Specialization
Citations

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

Fields of papers citing papers by Aimal Khan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Aimal Khan

This figure shows the co-authorship network connecting the top 25 collaborators of Aimal Khan. A scholar is included among the top collaborators of Aimal 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 Aimal Khan. Aimal 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
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Khan, Aimal & Thomas Greiner. (2023). Symbolic AI for External Magnetic Interference Classification in Magnetostrictive Position Sensors. 185–188. 2 indexed citations
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Khawaja, Sajid Gul, et al.. (2022). Machine Learning and Signal Processing Based Analysis of sEMG Signals for Daily Action Classification. IEEE Access. 10. 40506–40516. 8 indexed citations
7.
Khan, Muhammad Attique, Abdullah Alqahtani, Aimal Khan, et al.. (2022). Cucumber Leaf Diseases Recognition Using Multi Level Deep Entropy-ELM Feature Selection. Applied Sciences. 12(2). 593–593. 56 indexed citations
8.
Shah, Faiz Ali, Muhammad Attique Khan, Muhammad Sharif, et al.. (2021). A Cascaded Design of Best Features Selection for Fruit Diseases Recognition. Computers, materials & continua/Computers, materials & continua (Print). 70(1). 1491–1507. 15 indexed citations
9.
Khan, Aimal, et al.. (2020). Towards the Selection of the Best Machine Learning Techniques and Methods for Urinalysis. 127–133. 3 indexed citations
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Rehman, Saad, et al.. (2019). Approximate Proximal Gradient-Based Correlation Filter for Target Tracking in Videos: A Unified Approach. Arabian Journal for Science and Engineering. 44(11). 9363–9380. 6 indexed citations
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Khan, Aimal, et al.. (2019). Denoising The Wireless Channel Corrupted Images Using Machine Learning. 1–6. 3 indexed citations
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Qamar, Usman, et al.. (2019). Machine Learning Techniques for Heart Disease Datasets. 27–35. 27 indexed citations
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Ahmad, Ayaz, et al.. (2018). Energy‐efficient resource allocation and RRH association in multitier 5G H‐CRANs. Transactions on Emerging Telecommunications Technologies. 30(1). 16 indexed citations
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Khan, Aimal, Saad Rehman, Muhammad Zahid Abbas, & Ayaz Ahmad. (2018). On the mutual information of relaying protocols. Physical Communication. 30. 33–42. 6 indexed citations
15.
Shahriar, Nashid, Reaz Ahmed, Shihabur Rahman Chowdhury, et al.. (2017). Generalized Recovery From Node Failure in Virtual Network Embedding. IEEE Transactions on Network and Service Management. 14(2). 261–274. 38 indexed citations
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Shahriar, Nashid, Shihabur Rahman Chowdhury, Reaz Ahmed, et al.. (2017). Joint backup capacity allocation and embedding for survivable virtual networks. 1–9. 4 indexed citations
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Ghaznavi, Milad, Aimal Khan, Nashid Shahriar, et al.. (2015). Elastic virtual network function placement. 255–260. 156 indexed citations
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Khan, Aimal & Volker Kuehn. (2010). Optimizing ARQ strategies in relay networks. HAL (Le Centre pour la Communication Scientifique Directe). 520–527. 2 indexed citations
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Khan, Aimal & Volker Kühn. (2010). On the performance of adaptive relaying with ARQ. 121–126. 4 indexed citations
20.
Broadwater, Robert, et al.. (1988). Power flow analysis of unbalanced multiphase radial distribution systems. Electric Power Systems Research. 14(1). 23–33. 33 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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