Mohammad Ghoniem

27 papers receiving 779 citations

Peers

Mohammad Ghoniem
Comparison fields: 5 of 97
  • Computer Vision and Pattern Recognition 547
  • Statistical and Nonlinear Physics 217
  • Signal Processing 102
  • Computational Mathematics 4
  • Artificial Intelligence 174
Replace Ilir Jusufi with:
Ilir Jusufi Sweden
David Auber France
Hans‐Jörg Schulz Germany
Kai Xu United Kingdom
Conglei Shi Hong Kong
Philippe Castagliola France
Chris Muelder United States
R. Amar United States
Emmanuel Pietriga France
Elizabeth Hetzler United States
Mohammad Ghoniem relative to Ilir Jusufi Sweden Ilir Jusufi's profile →
Citations per field
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Ilir Jusufi · 1×
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 29 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2005211
2 2005199
3 2007101
4 201969
5 201759
6 200827
7 200723
8 201618
9 201716
10 200814
11 20158
12 20138
13 20236
14 20246
15 20205
16 20145
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 Experimental and Cognitive Psychology, having authored 29 papers that have together received 801 indexed citations. Recurring topics across this work include Data Visualization and Analytics (16 papers), Complex Network Analysis Techniques (6 papers), Mental Health Research Topics (4 papers), Video Analysis and Summarization (4 papers), Data Management and Algorithms (3 papers), Advanced Clustering Algorithms Research (2 papers), Anomaly Detection Techniques and Applications (2 papers) and Bioinformatics and Genomic Networks (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (547 citations), Statistical and Nonlinear Physics (217 citations), Signal Processing (102 citations), Computational Mathematics (4 citations) and Artificial Intelligence (174 citations). Mohammad Ghoniem has collaborated with scholars based in Luxembourg, France and United States. Frequent co-authors include Philippe Castagliola, Jean‐Daniel Fekete, Benoît Otjacques, William Ribarsky, Fintan McGee, Guy Mélançon, Robert Kosara, Remco Chang, Daniel Kern and Agus Sudjianto. Their work appears in journals such as Information Visualization, Computer Graphics Forum, Scientific Reports, BMC Medical Research Methodology and Applied Network Science.

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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