Lukas Gianinazzi

59 total papers · 601 total citations
11 papers, 207 citations indexed

About

Lukas Gianinazzi is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, Lukas Gianinazzi has authored 11 papers receiving a total of 207 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Computer Vision and Pattern Recognition, 5 papers in Artificial Intelligence and 4 papers in Computer Networks and Communications. Recurrent topics in Lukas Gianinazzi's work include Graph Theory and Algorithms (4 papers), Complexity and Algorithms in Graphs (4 papers) and Advanced Graph Neural Networks (4 papers). Lukas Gianinazzi is often cited by papers focused on Graph Theory and Algorithms (4 papers), Complexity and Algorithms in Graphs (4 papers) and Advanced Graph Neural Networks (4 papers). Lukas Gianinazzi collaborates with scholars based in Switzerland, Poland and United States. Lukas Gianinazzi's co-authors include Torsten Hoefler, Maciej Besta, H. Niewiadomski, Michał Podstawski, Robert Gerstenberger, Saleh Ashkboos, Grzegorz Kwaśniewski, Simon Weber, Nikoli Dryden and Leighton Wilson and has published in prestigious journals such as Proceedings of the VLDB Endowment, ACM SIGPLAN Notices and IRIS Research product catalog (Sapienza University of Rome).

In The Last Decade

Lukas Gianinazzi

10 papers receiving 200 citations

Hit Papers

Graph of Thoughts: Solvin... 2024 2026 2024 50 100 150

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Lukas Gianinazzi 126 49 28 27 19 11 207
Mostofa Patwary 146 1.2× 39 0.8× 19 0.7× 26 1.0× 16 0.8× 10 207
Arun Iyer 150 1.2× 30 0.6× 36 1.3× 103 3.8× 4 0.2× 13 241
Akshay Agrawal 81 0.6× 29 0.6× 34 1.2× 32 1.2× 8 0.4× 16 197
Hao Liang 106 0.8× 37 0.8× 29 1.0× 14 0.5× 8 0.4× 17 172
Hyokun Yun 92 0.7× 59 1.2× 22 0.8× 53 2.0× 7 0.4× 7 162
Qingxiu Dong 186 1.5× 45 0.9× 17 0.6× 35 1.3× 2 0.1× 11 266
H. Niewiadomski 98 0.8× 27 0.6× 12 0.4× 20 0.7× 3 0.2× 7 170
Huasha Zhao 105 0.8× 47 1.0× 50 1.8× 52 1.9× 6 0.3× 12 170
Yuxin Chen 150 1.2× 57 1.2× 45 1.6× 14 0.5× 13 0.7× 19 210
Yujia Liu 151 1.2× 118 2.4× 18 0.6× 22 0.8× 15 0.8× 15 254

Countries citing papers authored by Lukas Gianinazzi

Since Specialization
Citations

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

Fields of papers citing papers by Lukas Gianinazzi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lukas Gianinazzi

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

All Works

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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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