Mohammad Ghoniem

30 papers receiving 884 citations

Peers

Mohammad Ghoniem
Comparison fields: 5 of 98
  • Computer Vision and Pattern Recognition 621
  • Statistical and Nonlinear Physics 247
  • Signal Processing 121
  • Computational Mathematics 4
  • Computer Graphics and Computer-Aided Design 22
Replace Ilir Jusufi with:
Ilir Jusufi Sweden
Conglei Shi Hong Kong
Philippe Castagliola France
Kai Xu Australia
Chris Muelder United States
Elizabeth Hetzler United States
David Auber France
Hans‐Jörg Schulz Germany
Dong Hyun Jeong United States
Masashi Toyoda Japan
Mohammad Ghoniem relative to Ilir Jusufi Sweden Ilir Jusufi's profile →
Citations per field
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Citations per year

Countries citing papers authored by Mohammad Ghoniem

Since Specialization
Citations

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

Fields of papers citing papers by Mohammad Ghoniem

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 32 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2005233
2 2005222
3 2007113
4 201975
5 201762
6 200840
7 200727
8 200824
9 201718
10 201618
11 201311
12 201510
13 20247
14 20147
15 20236
16 20206
17 20245
18 20215
19
Towards Visual Analytics of Multilayer Graphs for Digital Cultural Heritage
20164
20 20233

About Mohammad Ghoniem

Mohammad Ghoniem is a scholar working on Computer Vision and Pattern Recognition, Statistical and Nonlinear Physics, Artificial Intelligence, Signal Processing and Information Systems, having authored 32 papers that have together received 911 indexed citations. Recurring topics across this work include Data Visualization and Analytics (18 papers), Complex Network Analysis Techniques (7 papers), Video Analysis and Summarization (5 papers), Mental Health Research Topics (4 papers), Data Management and Algorithms (3 papers), Advanced Clustering Algorithms Research (2 papers), Data Mining Algorithms and Applications (2 papers) and Anomaly Detection Techniques and Applications (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (621 citations), Statistical and Nonlinear Physics (247 citations), Signal Processing (121 citations), Computational Mathematics (4 citations) and Computer Graphics and Computer-Aided Design (22 citations). Mohammad Ghoniem has collaborated with scholars based in Luxembourg, France and United States. Frequent co-authors include Jean‐Daniel Fekete, Philippe Castagliola, William Ribarsky, Benoît Otjacques, Evan A. Suma, Remco Chang, Fintan McGee, Robert Kosara, Daniel Kern and Caroline Ziemkiewicz. Their work appears in journals such as Information Visualization, Computer Graphics Forum, Frontiers in Public Health, Applied Network Science and IEEE Transactions on Visualization and Computer Graphics.

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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