Dan Jurca

729 citations
29 papers · 508 · h-index 11

Impact in

Papers in

Dan Jurca

28 papers receiving 482 citations

Peers

Dan Jurca
Comparison fields: 5 of 24
  • Computer Networks and Communications 412
  • Signal Processing 115
  • Computer Vision and Pattern Recognition 135
  • Electrical and Electronic Engineering 312
  • Information Systems 34
Replace Burak Görkemli with:
Burak Görkemli Türkiye
Srisakul Thakolsri Germany
Xiaofeng Xu China
Kristian Evensen Norway
Gaetano Carlucci Italy
Ashkan Nikravesh United States
Qinghua Wu China
Jie Hui United States
Stefan Holmer Italy
Zhourong Miao United States
Dan Jurca relative to Burak Görkemli Türkiye Burak Görkemli's profile →
Citations per field
00.5×3.3×
Burak Görkemli · 1×
Citations per year

Countries citing papers authored by Dan Jurca

Since Specialization
Citations

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

Fields of papers citing papers by Dan Jurca

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Dan Jurca, 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 Dan Jurca Line = papers co-authored together Dan Jurca 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 2007104
2 201288
3 200761
4 200736
5 200936
6 201028
7 201018
8 201116
9 200612
10 200712
11
MEDIA-SPECIFIC RATE ALLOCATION IN MULTIPATH NETWORKS
200512
12 200910
13 20059
14 20107
15 20107
16 20116
17 20066
18 20085
19 20055
20 20065

About Dan Jurca

Dan Jurca is a scholar working on Computer Networks and Communications, Electrical and Electronic Engineering, Computer Vision and Pattern Recognition, Signal Processing and Information Systems, having authored 29 papers that have together received 508 indexed citations. Recurring topics across this work include Advanced Wireless Network Optimization (16 papers), Network Traffic and Congestion Control (11 papers), Image and Video Quality Assessment (10 papers), Video Coding and Compression Technologies (10 papers), Caching and Content Delivery (8 papers), Peer-to-Peer Network Technologies (7 papers), Cooperative Communication and Network Coding (6 papers) and Software-Defined Networks and 5G (4 papers). The work is most often cited by research in Computer Networks and Communications (412 citations), Signal Processing (115 citations), Computer Vision and Pattern Recognition (135 citations), Electrical and Electronic Engineering (312 citations) and Information Systems (34 citations). Dan Jurca has collaborated with scholars based in Switzerland, Germany and France. Frequent co-authors include Pascal Frossard, Wolfgang Kellerer, Ashiq Khan, Alf Zugenmaier, Joerg Widmer, Daniele Munaretto, Aleksandar Jovanović, Jacob Chakareski, Srisakul Thakolsri and Rolf Stadler. Their work appears in journals such as IEEE Communications Magazine, IEEE Transactions on Multimedia, Journal of Zhejiang University. Science A, Signal Processing Image Communication and IEEE Transactions on Circuits and Systems for Video Technology.

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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