Lukas Gianinazzi

626 total citations · 1 hit paper
14 papers, 225 citations indexed

About

Lukas Gianinazzi is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computer Networks and Communications. According to data from OpenAlex, Lukas Gianinazzi has authored 14 papers receiving a total of 225 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 5 papers in Computer Vision and Pattern Recognition and 4 papers in Computer Networks and Communications. Recurrent topics in Lukas Gianinazzi's work include Advanced Graph Neural Networks (6 papers), Graph Theory and Algorithms (4 papers) and Complexity and Algorithms in Graphs (4 papers). Lukas Gianinazzi is often cited by papers focused on Advanced Graph Neural Networks (6 papers), Graph Theory and Algorithms (4 papers) and Complexity and Algorithms in Graphs (4 papers). Lukas Gianinazzi collaborates with scholars based in Switzerland, United States and Poland. Lukas Gianinazzi's co-authors include Torsten Hoefler, Maciej Besta, Michał Podstawski, Ales Kubicek, Robert Gerstenberger, Piotr Nyczyk, Nils Blach, H. Niewiadomski, Grzegorz Kwaśniewski and Nikoli Dryden and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, NeuroImage and Proceedings of the VLDB Endowment.

In The Last Decade

Lukas Gianinazzi

10 papers receiving 216 citations

Hit Papers

Graph of Thoughts: Solving Elaborate Problems with Large ... 2024 2026 2025 2024 50 100 150
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Graph of Thoughts: Solving Elaborate Problems with Large Language Models
    2024 161 citations Maciej Besta, Nils Blach et al. Proceedings of the AAAI Conference on Artificial Intelligence profile →

Peers

Lukas Gianinazzi
Xuming Hu China
Qingxiu Dong China
Yuxian Gu China
Jianheng Tang China
Mohamed Yehia Dahab Saudi Arabia
Chen Gao China
Eli Lifland United States
Mengyu Zhou China
Ahmed Guessoum Algeria
Xuming Hu China
Lukas Gianinazzi
Citations per year, relative to Lukas Gianinazzi Lukas Gianinazzi (= 1×) peers Xuming Hu

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

14 of 14 papers shown
1.
Gianinazzi, Lukas, Cornelia Hagmann, Raimund Kottke, et al.. (2025). Atlas-independent brain connectome analysis at voxel-level granularity: graph convolutional networks for etiology classification in newborns. NeuroImage. 322. 121568–121568.
2.
Besta, Maciej, et al.. (2025). Demystifying Higher-Order Graph Neural Networks. IEEE Transactions on Pattern Analysis and Machine Intelligence. 48(3). 2544–2565.
3.
Besta, Maciej, Zhenyu Zhang, Robert Gerstenberger, et al.. (2025). Demystifying Chains, Trees, and Graphs of Thoughts. IEEE Transactions on Pattern Analysis and Machine Intelligence. 47(12). 10967–10989.
4.
Gianinazzi, Lukas, et al.. (2024). Near-Optimal Wafer-Scale Reduce. IRIS Research product catalog (Sapienza University of Rome). 334–347. 5 indexed citations
5.
Ben‐Nun, Tal, et al.. (2024). Low-Depth Spatial Tree Algorithms. 1 indexed citations
6.
Besta, Maciej, Nils Blach, Ales Kubicek, et al.. (2024). Graph of Thoughts: Solving Elaborate Problems with Large Language Models. Proceedings of the AAAI Conference on Artificial Intelligence. 38(16). 17682–17690. 161 indexed citations breakdown →
7.
Besta, Maciej, Robert Gerstenberger, Paolo Sylos Labini, et al.. (2023). High-Performance and Programmable Attentional Graph Neural Networks with Global Tensor Formulations. Institutional Research Information System (Università degli Studi di Trento). 1–16. 4 indexed citations
8.
Matteis, Tiziano De, Lukas Gianinazzi, Johannes de Fine Licht, & Torsten Hoefler. (2023). Streaming Task Graph Scheduling for Dataflow Architectures. 225–237. 1 indexed citations
9.
Besta, Maciej, Grzegorz Kwaśniewski, Saleh Ashkboos, et al.. (2022). Motif Prediction with Graph Neural Networks. Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. 35–45. 21 indexed citations
10.
Gianinazzi, Lukas, et al.. (2021). Parallel Minimum Cuts in Near-linear Work and Low Depth. 8(2). 1–20.
11.
Besta, Maciej, Grzegorz Kwaśniewski, Lukas Gianinazzi, et al.. (2021). GraphMineSuite. Proceedings of the VLDB Endowment. 14(11). 1922–1935. 7 indexed citations
12.
Besta, Maciej, et al.. (2019). Slim graph. 1–25. 17 indexed citations
13.
Gianinazzi, Lukas, et al.. (2018). Communication-avoiding parallel minimum cuts and connected components. ACM SIGPLAN Notices. 53(1). 219–232. 3 indexed citations
14.
Gianinazzi, Lukas, et al.. (2018). Communication-avoiding parallel minimum cuts and connected components. 219–232. 5 indexed citations

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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