Majd Sakr

760 citations
35 papers · 348 indexed · h-index 11
Topics
Cloud Computing and Resource Management (10 papers)IoT and Edge/Fog Computing (7 papers)AI in Service Interactions (7 papers)

In The Last Decade

Majd Sakr

34 papers receiving 341 citations

Peers

Majd Sakr
Comparison fields: 5 of 63
  • Artificial Intelligence 111
  • Information Systems 97
  • Computer Science Applications 96
  • Social Psychology 82
  • Computer Networks and Communications 51
Replace Maxim Mozgovoy with:
Maxim Mozgovoy Japan
Traian Rebedea Romania
Majd Sakr United States
Ian Drosos United States
Ram B. Basnet United States
Luciana Benotti Argentina
Austin Z. Henley United States
Vidya Rajaram United States
April Yi Wang United States
Leandro Silva Galvão de Carvalho Brazil
Majd Sakr relative to Maxim Mozgovoy Japan Maxim Mozgovoy's profile →
Citations per field
00.5×6.4×
Maxim Mozgovoy · 1×
Citations per year

Countries citing papers authored by Majd Sakr

Since Specialization
Citations

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

Fields of papers citing papers by Majd Sakr

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Majd Sakr

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

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 1
3 64
4 6
5 8
6
Creating Opportunities for Transactive Exchange for Learning in Performance-Oriented Team Projects.
1
7 4
8 3
9 12
10 5
11 5
12 3
13 16
14 11
15 7
16 40
17 11
18 8
19 6
20
Predicting Multiprocessor Memory Access Patterns with Learning Models
16

About Majd Sakr

Majd Sakr is a scholar working on Computer Science Applications, Information Systems and Software, having authored 35 papers that have together received 348 indexed citations. Recurring topics across this work include Cloud Computing and Resource Management (10 papers), IoT and Edge/Fog Computing (7 papers) and AI in Service Interactions (7 papers). The work is most often cited by research in Computer Science Applications (96 citations), Health Informatics (19 citations) and Information Systems (97 citations). Majd Sakr has collaborated with scholars based in United States, Qatar and United Kingdom. Frequent co-authors include Christopher Bogart, Maxim Makatchev, Reid Simmons, Yifan Song, Jaromír Šavelka, Arav Agarwal, Brett Browning, Fan Zhang, Donald M. Chiarulli and Steven P. Levitan. Their work appears in journals such as Proceedings of the IEEE, AI Magazine and IEEE Transactions on Cloud Computing.

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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