Hammad Afzal

1.9k citations
82 papers · 1.2k · h-index 19

Impact in

Papers in

    • Topic Modeling 11
    • Internet Traffic Analysis and Secure E-voting 8
    • Sentiment Analysis and Opinion Mining 7
    • Spam and Phishing Detection 8
    • Software Engineering Research 5

Hammad Afzal

74 papers receiving 1.1k citations

Peers

Hammad Afzal
Comparison fields: 5 of 120
  • Health Informatics 41
  • General Dentistry 29
  • Signal Processing 156
  • Information Systems 289
  • Artificial Intelligence 377
Replace Sushruta Mishra with:
Sushruta Mishra India
Plácido Rogério Pinheiro Brazil
Suliman Mohamed Fati Saudi Arabia
Hrudaya Kumar Tripathy India
Noor Akhmad Setiawan Indonesia
Sachin Ahuja India
Muhammad Fermi Pasha Malaysia
Octavio Loyola‐González Mexico
Antoni Ligęza Poland
Omar Alfandi United Arab Emirates
Hammad Afzal relative to Sushruta Mishra India Sushruta Mishra's profile →
Citations per field
00.5×10×15×20×23.7×
Sushruta Mishra · 1×
Citations per year

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-authors

The 25 scholars most cited alongside Hammad Afzal, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Hammad Afzal Line = papers co-authored together Hammad Afzal links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 82 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020149
2 201871
3 201762
4 201756
5 202255
6 202242
7 202142
8 201841
9 202339
10 201238
11 201934
12 201934
13 202331
14 202131
15 201926
16 201925
17 201825
18 202122
19 201819
20 202018

About Hammad Afzal

Hammad Afzal is a scholar working on Artificial Intelligence, Information Systems, Computer Networks and Communications, Computer Vision and Pattern Recognition and Signal Processing, having authored 82 papers that have together received 1.2k indexed citations. Recurring topics across this work include Advanced Malware Detection Techniques (11 papers), Topic Modeling (11 papers), Network Security and Intrusion Detection (9 papers), Spam and Phishing Detection (8 papers), Internet Traffic Analysis and Secure E-voting (8 papers), Sentiment Analysis and Opinion Mining (7 papers), IoT and Edge/Fog Computing (6 papers) and Software Engineering Research (5 papers). The work is most often cited by research in Health Informatics (41 citations), General Dentistry (29 citations), Signal Processing (156 citations), Information Systems (289 citations) and Artificial Intelligence (377 citations). Hammad Afzal has collaborated with scholars based in Pakistan, United Kingdom and South Korea. Frequent co-authors include Haider Abbas, Naima Iltaf, Waseem Iqbal, Raheel Nawaz, Muhammad Faisal Amjad, Yawar Abbas Bangash, Imran Siddiqi, Imran Rashid, Mehreen Ahmed and Isabel de la Torre Díez. Their work appears in journals such as IEEE Access, Sensors, Neural Computing and Applications, Computer Communications and Neurocomputing.

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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