Malik M. Khan

504 total citations
17 papers, 302 citations indexed

About

Malik M. Khan is a scholar working on Computer Networks and Communications, Information Systems and Hardware and Architecture. According to data from OpenAlex, Malik M. Khan has authored 17 papers receiving a total of 302 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Computer Networks and Communications, 8 papers in Information Systems and 5 papers in Hardware and Architecture. Recurrent topics in Malik M. Khan's work include Parallel Computing and Optimization Techniques (5 papers), Spam and Phishing Detection (3 papers) and Sentiment Analysis and Opinion Mining (2 papers). Malik M. Khan is often cited by papers focused on Parallel Computing and Optimization Techniques (5 papers), Spam and Phishing Detection (3 papers) and Sentiment Analysis and Opinion Mining (2 papers). Malik M. Khan collaborates with scholars based in Pakistan, United States and Kazakhstan. Malik M. Khan's co-authors include Saddaf Rubab, P.D. Alexander, Yawar Abbas Bangash, Mao Shan, E. Nebot, Haider Abbas, Stewart Worrall, Mary Hall, Protonu Basu and Ayesha Altaf and has published in prestigious journals such as Expert Systems with Applications, Sensors and IEEE Internet of Things Journal.

In The Last Decade

Malik M. Khan

17 papers receiving 285 citations

Peers

Malik M. Khan
Samia Bouzefrane France
Hong Min South Korea
Chris Thompson United States
Jinghan Sun China
Lei Miao United States
Smys S. India
Petr Fiedler Czechia
Maman Abdurohman Indonesia
Samia Bouzefrane France
Malik M. Khan
Citations per year, relative to Malik M. Khan Malik M. Khan (= 1×) peers Samia Bouzefrane

Countries citing papers authored by Malik M. Khan

Since Specialization
Citations

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

Fields of papers citing papers by Malik M. Khan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Malik M. Khan

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

All Works

17 of 17 papers shown
1.
Rubab, Saddaf, Malik M. Khan, Fahim Uddin, Yawar Abbas Bangash, & Syed Ali Ammar Taqvi. (2022). A Study on AI‐based Waste Management Strategies for the COVID‐19 Pandemic. ChemBioEng Reviews. 9(2). 212–226. 26 indexed citations
2.
Rubab, Saddaf, et al.. (2022). Hybrid Approach for Shelf Monitoring and Planogram Compliance (Hyb-SMPC) in Retails Using Deep Learning and Computer Vision. Mathematical Problems in Engineering. 2022. 1–18. 8 indexed citations
3.
Rubab, Saddaf, et al.. (2022). S-RAP: relevance-aware QoS prediction in web-services and user contexts. Knowledge and Information Systems. 64(7). 1997–2022. 4 indexed citations
4.
Rubab, Saddaf, et al.. (2022). Detection and prediction of traffic accidents using deep learning techniques. Cluster Computing. 26(1). 477–493. 40 indexed citations
5.
Abbas, Haider, et al.. (2022). A framework to predict early news popularity using deep temporal propagation patterns. Expert Systems with Applications. 195. 116496–116496. 6 indexed citations
6.
Masood, Asif, et al.. (2021). Textual analysis of traitor-based dataset through semi supervised machine learning. Future Generation Computer Systems. 125. 652–660. 11 indexed citations
7.
Altaf, Ayesha, et al.. (2021). Mitigating service-oriented attacks using context-based trust for smart cities in IoT networks. Journal of Systems Architecture. 115. 102028–102028. 23 indexed citations
8.
Rubab, Saddaf, et al.. (2021). An Automated System to Predict Popular Cybersecurity News Using Document Embeddings. Computer Modeling in Engineering & Sciences. 127(2). 533–547. 1 indexed citations
9.
Shan, Mao, et al.. (2020). Demonstrations of Cooperative Perception: Safety and Robustness in Connected and Automated Vehicle Operations. Sensors. 21(1). 200–200. 80 indexed citations
10.
Altaf, Ayesha, Haider Abbas, Faiza Iqbal, Malik M. Khan, & Mahmoud Daneshmand. (2020). Robust, Secure, and Adaptive Trust-Oriented Service Selection in IoT-Based Smart Buildings. IEEE Internet of Things Journal. 8(9). 7497–7509. 21 indexed citations
11.
12.
Khan, Malik M. & Anne C. Elster. (2016). Characterizing numascale clusters with GPUs: MPI-based and GPU interconnect benchmarks. 840–847. 2 indexed citations
13.
Khan, Malik M., et al.. (2014). Tracking Occluded Objects Using Kalman Filter and Color Information. International Journal of Computer Theory and Engineering. 6(5). 438–442. 9 indexed citations
14.
Kim, Intaek, et al.. (2014). Multi-Target Tracking Using Color Information. International Journal of Computer and Communication Engineering. 3(1). 11–15. 7 indexed citations
15.
Basu, Protonu, Mary Hall, Malik M. Khan, et al.. (2013). Towards making autotuning mainstream. The International Journal of High Performance Computing Applications. 27(4). 379–393. 15 indexed citations
16.
Khan, Malik M., Protonu Basu, Gabe Rudy, et al.. (2013). A script-based autotuning compiler system to generate high-performance CUDA code. ACM Transactions on Architecture and Code Optimization. 9(4). 1–25. 37 indexed citations
17.
Hall, Mary, Aiichiro Nakano, & Malik M. Khan. (2012). Autotuning, code generation and optimizing compiler technology for gpus. 4 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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2026