Julien Siebert

20 papers receiving 444 citations

Peers

Julien Siebert
Comparison fields: 5 of 92
  • Software 56
  • Health Informatics 11
  • Computer Networks and Communications 164
  • Statistical and Nonlinear Physics 81
  • Information Systems 114
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Matej Balog United Kingdom
Yu Wu China
Xiaozhi Wang China
Kazuo Misue Japan
Yuanshun Yao United States
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Citations per year

Countries citing papers authored by Julien Siebert

Since Specialization
Citations

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

Fields of papers citing papers by Julien Siebert

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown
#Work
1 2021157
2 201570
3 202258
4 202136
5 202018
6 202315
7 201415
8 200414
9 201513
10 202312
11 201511
12 20029
13 20218
14 20057
15 20107
16 20243
17
Towards standards for Pervasive Computing evaluation: using the multi-model and multi-agent paradigms for mobility
20081
18
Algorithm Accountability, Algorithm Literacy and the hidden assumptions from algorithms.
20181
19
AA4MM coordination model and event-B specification
20091
20 20211

About Julien Siebert

Julien Siebert is a scholar working on Computer Networks and Communications, Information Systems, Statistical and Nonlinear Physics, Information Systems and Management and Artificial Intelligence, having authored 20 papers that have together received 457 indexed citations. Recurring topics across this work include Nonlinear Dynamics and Pattern Formation (4 papers), Software Engineering Research (4 papers), Statistical Mechanics and Entropy (3 papers), Software Reliability and Analysis Research (2 papers), Scientific Computing and Data Management (2 papers), Cosmology and Gravitation Theories (2 papers), Slime Mold and Myxomycetes Research (2 papers) and Advanced Thermodynamics and Statistical Mechanics (2 papers). The work is most often cited by research in Software (56 citations), Health Informatics (11 citations), Computer Networks and Communications (164 citations), Statistical and Nonlinear Physics (81 citations) and Information Systems (114 citations). Julien Siebert has collaborated with scholars based in Germany, France and Japan. Frequent co-authors include Hui Han, Eckehard Schöll, Adam Trendowicz, Xavier Franch, Anna Maria Vollmer, Silverio Martínez‐Fernández, Justus Bogner, Stefan Wagner, Marc Oriol and Anna Zakharova. Their work appears in journals such as Nuclear Physics B, Information and Software Technology, IEEE Software, Europhysics Letters (EPL) and Chaos An Interdisciplinary Journal of Nonlinear 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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