Hammad Afzal

1.9k total citations
82 papers, 1.2k citations indexed

About

Hammad Afzal is a scholar working on Artificial Intelligence, Information Systems and Computer Networks and Communications. According to data from OpenAlex, Hammad Afzal has authored 82 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 39 papers in Artificial Intelligence, 34 papers in Information Systems and 20 papers in Computer Networks and Communications. Recurrent topics in Hammad Afzal's work include Topic Modeling (11 papers), Advanced Malware Detection Techniques (11 papers) and Network Security and Intrusion Detection (9 papers). Hammad Afzal is often cited by papers focused on Topic Modeling (11 papers), Advanced Malware Detection Techniques (11 papers) and Network Security and Intrusion Detection (9 papers). Hammad Afzal collaborates with scholars based in Pakistan, United Kingdom and South Korea. Hammad Afzal's co-authors include Haider Abbas, Naima Iltaf, Waseem Iqbal, Raheel Nawaz, Muhammad Faisal Amjad, Yawar Abbas Bangash, Imran Siddiqi, Imran Rashid, Mehreen Ahmed and Imran Shafi and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and IEEE Communications Surveys & Tutorials.

In The Last Decade

Hammad Afzal

74 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Hammad Afzal Pakistan	19	377	289	265	182	156	82	1.2k
Suliman Mohamed Fati Saudi Arabia	22	571 1.5×	205 0.7×	216 0.8×	199 1.1×	153 1.0×	74	1.6k
Retantyo Wardoyo Indonesia	16	625 1.7×	569 2.0×	84 0.3×	186 1.0×	51 0.3×	157	1.5k
Huiju Wang China	12	217 0.6×	773 2.7×	470 1.8×	78 0.4×	59 0.4×	25	1.1k
Muhammad Fermi Pasha Malaysia	17	346 0.9×	544 1.9×	442 1.7×	118 0.6×	82 0.5×	71	1.4k
Sushruta Mishra India	21	288 0.8×	149 0.5×	140 0.5×	155 0.9×	36 0.2×	87	1.1k
Irina V. Pustokhina Russia	19	367 1.0×	227 0.8×	330 1.2×	287 1.6×	64 0.4×	63	1.3k
Octavio Loyola‐González Mexico	17	612 1.6×	320 1.1×	169 0.6×	135 0.7×	244 1.6×	50	1.3k
Sachin Ahuja India	13	411 1.1×	144 0.5×	182 0.7×	103 0.6×	81 0.5×	98	1.0k
Denis A. Pustokhin Russia	19	362 1.0×	220 0.8×	328 1.2×	287 1.6×	64 0.4×	55	1.2k
Antoni Ligęza Poland	14	716 1.9×	314 1.1×	206 0.8×	122 0.7×	74 0.5×	75	1.5k

Countries citing papers authored by Hammad Afzal

Since Specialization

Citations

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

Fields of papers citing papers by Hammad Afzal

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hammad Afzal

This figure shows the co-authorship network connecting the top 25 collaborators of Hammad Afzal. A scholar is included among the top collaborators of Hammad Afzal 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 Hammad Afzal. Hammad Afzal 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

Afzal, Hammad, et al.. (2025). Enhancing multiple sclerosis diagnosis and prognosis through a dual Patch-Wise CNN architecture. Biomedical Signal Processing and Control. 107. 107835–107835.

Afzal, Hammad, et al.. (2024). A light-weight deep learning framework for Low Light Image Enhancement. Neurocomputing. 621. 129236–129236. 4 indexed citations

Anwar, Zeeshan, Hammad Afzal, Taher Al‐Shehari, et al.. (2024). Mining the Opinions of Software Developers for Improved Project Insights: Harnessing the Power of Transfer Learning. IEEE Access. 12. 65942–65955. 2 indexed citations

Anwar, Zeeshan, et al.. (2024). Collaborative Solutions to Software Architecture Challenges Faced by IT Professionals. International Journal of Human Capital and Information Technology Professionals. 15(1). 1–29. 1 indexed citations

Al‐Shehari, Taher, Domenico Rosaci, Muna Al‐Razgan, et al.. (2024). Enhancing Insider Threat Detection in Imbalanced Cybersecurity Settings Using the Density-Based Local Outlier Factor Algorithm. IEEE Access. 12. 34820–34834. 10 indexed citations

Anwar, Zeeshan, et al.. (2024). Fuzzy ensemble of fined tuned BERT models for domain-specific sentiment analysis of software engineering dataset. PLoS ONE. 19(5). e0300279–e0300279. 2 indexed citations

Afzal, Hammad, et al.. (2024). Low Resource Summarization using Pre-trained Language Models. ACM Transactions on Asian and Low-Resource Language Information Processing. 23(10). 1–19. 7 indexed citations

Shafi, Imran, et al.. (2023). Deep Learning-Based Multiclass Instance Segmentation for Dental Lesion Detection. Healthcare. 11(3). 347–347. 39 indexed citations

Afzal, Hammad, Taher Al‐Shehari, Muna Al‐Razgan, et al.. (2023). Detection and Classification of Temporal Changes for Citrus Canker Growth Rate Using Deep Learning. IEEE Access. 11. 127637–127650. 5 indexed citations

10.

Anwar, Zeeshan, Hammad Afzal, Ali Ahsan, Naima Iltaf, & Ayesha Maqbool. (2023). A novel hybrid CNN-LSTM approach for assessing StackOverflow post quality. Journal of Intelligent Systems. 32(1). 6 indexed citations

11.

Shafi, Imran, Hammad Afzal, Isabel de la Torre Díez, et al.. (2023). A Comprehensive Review of Recent Advances in Artificial Intelligence for Dentistry E-Health. Diagnostics. 13(13). 2196–2196. 31 indexed citations

12.

Afzal, Hammad, et al.. (2023). Detection and Analysis of Mental Health Illness using Social Media. 34–41. 1 indexed citations

13.

Naveed, Muhammad, et al.. (2022). Depression Detection Based on Hybrid Deep Learning SSCL Framework Using Self-Attention Mechanism: An Application to Social Networking Data. Sensors. 22(24). 9775–9775. 42 indexed citations

14.

Afzal, Hammad, et al.. (2021). Identification of HATE speech tweets in Pashto language using Machine Learning techniques. International Journal of Advanced Trends in Computer Science and Engineering. 10(3). 1501–1508. 2 indexed citations

15.

Rashid, Imran, et al.. (2020). SS7 Vulnerabilities—A Survey and Implementation of Machine Learning vs Rule Based Filtering for Detection of SS7 Network Attacks. IEEE Communications Surveys & Tutorials. 22(2). 1337–1371. 149 indexed citations

16.

Iqbal, Waseem, et al.. (2019). Forensic Analysis of Tor Browser: A Case Study for Privacy and Anonymity on the Web. Forensic Science International. 299. 59–73. 25 indexed citations

17.

Afzal, Hammad, et al.. (2018). A Multi-Classifier Framework for Open Source Malware Forensics. 106–111. 6 indexed citations

18.

Arif, Omar, et al.. (2018). A Framework to Estimate the Nutritional Value of Food in Real Time Using Deep Learning Techniques. IEEE Access. 7. 2643–2652. 71 indexed citations

19.

Afzal, Hammad, James Eales, Robert Stevens, & Goran Nenadić. (2011). Mining semantic networks of bioinformatics e-resources from the literature. Journal of Biomedical Semantics. 2(S1). S4–S4. 4 indexed citations

20.

Afzal, Hammad, James Eales, Robert Stevens, & Goran Nenadić. (2009). Mining semantic networks of bioinformatics e-resources from the literature. Research Explorer (The University of Manchester). 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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