Hani Mahdi

582 citations
37 papers · 292 · h-index 8

Impact in

Papers in

Hani Mahdi

32 papers receiving 272 citations

Peers

Hani Mahdi
Comparison fields: 5 of 61
  • Computer Networks and Communications 108
  • Information Systems 101
  • Health Information Management 15
  • Computer Vision and Pattern Recognition 66
  • Computer Science Applications 15
Replace Ramanathan Lakshmanan with:
Ramanathan Lakshmanan India
Ji Su Park South Korea
Rahul Neware India
Abdel-Hamid M. Emara Saudi Arabia
Ajay Reddy Yeruva India
J. Arokia Renjit India
Md Masum Billah Bangladesh
D. Selvaraj India
A.K.M. Muzahidul Islam Bangladesh
Muhammad Abul Hassan Pakistan
Hani Mahdi relative to Ramanathan Lakshmanan India Ramanathan Lakshmanan's profile →
Citations per field
00.5×1.5×2.4×
Ramanathan Lakshmanan · 1×
Citations per year

Countries citing papers authored by Hani Mahdi

Since Specialization
Citations

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

Fields of papers citing papers by Hani Mahdi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Hani Mahdi, 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 Hani Mahdi Line = papers co-authored together Hani Mahdi links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201982
2 201876
3 202316
4 201014
5 200312
6 202411
7 20177
8 20157
9 20086
10 20116
11 20194
12 20104
13 20204
14 20104
15 20184
16 20034
17 20054
18 20214
19 20253
20 20153

About Hani Mahdi

Hani Mahdi is a scholar working on Computer Vision and Pattern Recognition, Information Systems, Artificial Intelligence, Electrical and Electronic Engineering and Computer Networks and Communications, having authored 37 papers that have together received 292 indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (6 papers), Neuroscience and Neural Engineering (6 papers), Face and Expression Recognition (3 papers), Advanced Image Processing Techniques (3 papers), Cloud Computing and Resource Management (3 papers), Rough Sets and Fuzzy Logic (3 papers), Advanced Malware Detection Techniques (3 papers) and Generative Adversarial Networks and Image Synthesis (3 papers). The work is most often cited by research in Computer Networks and Communications (108 citations), Information Systems (101 citations), Health Information Management (15 citations), Computer Vision and Pattern Recognition (66 citations) and Computer Science Applications (15 citations). Hani Mahdi has collaborated with scholars based in Egypt, United States and United Arab Emirates. Frequent co-authors include Rawya Rizk, Basem E. Elnaghi, Alaa Tharwat, Aboul Ella Hassanien, Mohamed Elhoseny, Aly A. Farag, Mohammed Ghazal, Hazem M. Abbas, Seif Eldawlatly and R. A. Mohamed. Their work appears in journals such as IEEE Access, Brain Informatics, Artificial Intelligence Review, International Journal of Wireless Information Networks and IEEE Transactions on Neural Systems and Rehabilitation Engineering.

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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