Si‐Ahmed Naas

419 citations
9 papers · 244 indexed · 1 hit paper · h-index 5
Topics
Privacy-Preserving Technologies in Data (3 papers)IoT and Edge/Fog Computing (2 papers)Stochastic Gradient Optimization Techniques (2 papers)
Partner nations
FinlandJapanGermany

In The Last Decade

Si‐Ahmed Naas

8 papers receiving 237 citations

Hit Papers

Privacy‐preserving federated learning based on multi‐key ...2022202620232024202250100150200

Peers

Si‐Ahmed Naas
Comparison fields: 5 of 33
  • Artificial Intelligence 219
  • Electrical and Electronic Engineering 33
  • Sociology and Political Science 29
  • Information Systems 26
  • Computer Vision and Pattern Recognition 23
Replace Ahmed Moustafa with:
Ahmed Moustafa Japan
Yuanqin He China
Jiale Guo China
Virat Shejwalkar United States
Jinhyun So United States
Phillipp Schoppmann United States
Michael Zhu United States
HyungChul Kang South Korea
Chengfang Fang Singapore
Thibault Gisselbrecht France
Si‐Ahmed Naas relative to Ahmed Moustafa Japan Ahmed Moustafa's profile →
Citations per field
00.5×1.5×2.2×
Ahmed Moustafa · 1×
Citations per year

Countries citing papers authored by Si‐Ahmed Naas

Since Specialization
Citations

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

Fields of papers citing papers by Si‐Ahmed Naas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Si‐Ahmed Naas. 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 Si‐Ahmed Naas. The network helps show where Si‐Ahmed Naas may publish in the future.

Co-authorship network of co-authors of Si‐Ahmed Naas

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

All Works

9 of 9 papers shown
#WorkIndexed citations
1 4
2
Privacy‐preserving federated learning based on multi‐key homomorphic encryptionbreakdown →
222
3 4
4 0
5 6
6 1
7 2
8 4
9 1

About Si‐Ahmed Naas

Si‐Ahmed Naas is a scholar working on Computer Science Applications, Signal Processing and Human-Computer Interaction, having authored 9 papers that have together received 244 indexed citations. Recurring topics across this work include Privacy-Preserving Technologies in Data (3 papers), IoT and Edge/Fog Computing (2 papers) and Stochastic Gradient Optimization Techniques (2 papers). The work is most often cited by research in Artificial Intelligence (219 citations), Health Informatics (4 citations) and Computer Science Applications (15 citations). Si‐Ahmed Naas has collaborated with scholars based in Finland, Japan and Germany. Frequent co-authors include Stephan Sigg, Jing Ma, Xixiang Lyu, Yusheng Ji, Mario Di Francesco, Miloud Bagaa and Tarik Taleb. Their work appears in journals such as IEEE Access, IEEE Internet of Things Journal and International Journal of Intelligent Systems.

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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