Dror Maydan

2.3k citations
17 papers · 1.4k indexed · 1 hit paper · h-index 13

Dror Maydan

16 papers receiving 1.3k citations

Hit Papers

Parallel Programming in OpenMP7712000202620082017250500750

Peers

Dror Maydan
Comparison fields: 5 of 106
  • Hardware and Architecture 754
  • Computer Networks and Communications 621
  • Computer Graphics and Computer-Aided Design 66
  • Software 71
  • Computational Mathematics 5
Replace Naoya Maruyama with:
Naoya Maruyama Japan
Barbara Chapman United States
Sara S. Baghsorkhi United States
Timothy G. Mattson United States
Adam Beguelin United States
Sam S. Stone United States
Guochun Shi United States
Emilio L. Zapata Spain
Al Geist United States
Daehyun Kim United States
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Citations per field
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Citations per year

Countries citing papers authored by Dror Maydan

Since Specialization
Citations

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

Fields of papers citing papers by Dror Maydan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 21 scholars most cited alongside Dror Maydan, 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 Dror Maydan Line = papers co-authored together Dror Maydan links everyone, so they are left out of the graph.

All Works

17 of 17 papers shown
#Work
1 20114
2
Configurable Processors and the Evolution of System-on-Chip Design.
20050
3 200251
4 200162
5
Parallel Programming in OpenMPbreakdown →
2000771
6 199927
7 199810
8 199748
9 199713
10 199510
11 199419
12
Accurate analysis of array references
199318
13 1993106
14 199120
15 1991156
16 198961
17 198915

About Dror Maydan

Dror Maydan is a scholar working on Hardware and Architecture, Computer Networks and Communications, Computer Graphics and Computer-Aided Design, Information Systems and Computer Vision and Pattern Recognition, having authored 17 papers that have together received 1.4k indexed citations. Recurring topics across this work include Parallel Computing and Optimization Techniques (10 papers), Advanced Data Storage Technologies (8 papers), Distributed and Parallel Computing Systems (5 papers), Embedded Systems Design Techniques (4 papers), Cloud Computing and Resource Management (3 papers), Advanced Database Systems and Queries (3 papers), Distributed systems and fault tolerance (2 papers) and Statistical and numerical algorithms (1 paper). The work is most often cited by research in Hardware and Architecture (754 citations), Computer Networks and Communications (621 citations), Computer Graphics and Computer-Aided Design (66 citations), Software (71 citations) and Computational Mathematics (5 citations). Dror Maydan has collaborated with scholars based in United States and Israel. Frequent co-authors include Leonardo Dagum, Ramesh Menon, Monica S. Lam, John L. Hennessy, Saman Amarasinghe, Jitendra Malik, Michael E. Wolf, Chris Rowen, Albert Wang and Rohit Chandra. Their work appears in journals such as ACM SIGPLAN Notices, Pattern Recognition, IEEE Transactions on Pattern Analysis and Machine Intelligence, International Journal of Parallel Programming and Defense Technical Information Center (DTIC).

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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