Tim Verbelen

2.1k total citations · 1 hit paper
73 papers, 1.3k citations indexed

About

Tim Verbelen is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, Tim Verbelen has authored 73 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Computer Vision and Pattern Recognition, 25 papers in Artificial Intelligence and 21 papers in Computer Networks and Communications. Recurrent topics in Tim Verbelen's work include IoT and Edge/Fog Computing (18 papers), Advanced Neural Network Applications (11 papers) and Neural Networks and Applications (8 papers). Tim Verbelen is often cited by papers focused on IoT and Edge/Fog Computing (18 papers), Advanced Neural Network Applications (11 papers) and Neural Networks and Applications (8 papers). Tim Verbelen collaborates with scholars based in Belgium, United Kingdom and United States. Tim Verbelen's co-authors include Bart Dhoedt, Pieter Simoens, Filip De Turck, Steven Bohez, Christof Devriendt, Wout Weijtjens, Bert Vankeirsbilck, Sam Leroux, Tim J. Stevens and Gert De Sitter and has published in prestigious journals such as Nature Communications, Neuroscience & Biobehavioral Reviews and IEEE Access.

In The Last Decade

Tim Verbelen

71 papers receiving 1.2k citations

Hit Papers

Cloudlets 2012 2026 2016 2021 2012 50 100 150 200 250
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. Cloudlets
    2012 268 citations Tim Verbelen, Pieter Simoens et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Tim Verbelen Belgium 18 685 333 274 262 178 73 1.3k
Yun Ling China 15 469 0.7× 189 0.6× 224 0.8× 142 0.5× 305 1.7× 94 1.1k
Hongyu Yang China 19 689 1.0× 267 0.8× 194 0.7× 375 1.4× 621 3.5× 102 1.7k
Limei Peng South Korea 20 578 0.8× 265 0.8× 718 2.6× 165 0.6× 228 1.3× 160 1.5k
Shouxi Luo China 18 858 1.3× 341 1.0× 295 1.1× 248 0.9× 431 2.4× 77 1.6k
Lina Wang China 22 453 0.7× 483 1.5× 144 0.5× 614 2.3× 695 3.9× 199 1.8k
Тао Чен China 18 593 0.9× 273 0.8× 496 1.8× 554 2.1× 298 1.7× 133 1.8k
Penglin Dai China 24 937 1.4× 293 0.9× 583 2.1× 264 1.0× 462 2.6× 69 1.8k
Min Zhao China 18 448 0.7× 225 0.7× 369 1.3× 189 0.7× 178 1.0× 153 1.2k
Shaiful Jahari Hashim Malaysia 18 463 0.7× 206 0.6× 427 1.6× 147 0.6× 147 0.8× 142 1.2k
Rajesh M. Hegde India 21 358 0.5× 101 0.3× 506 1.8× 141 0.5× 396 2.2× 177 1.6k

Countries citing papers authored by Tim Verbelen

Since Specialization
Citations

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

Fields of papers citing papers by Tim Verbelen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tim Verbelen

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

All Works

20 of 20 papers shown
1.
Friston, Karl, Thomas Parr, Conor Heins, et al.. (2025). Gradient-Free De Novo Learning. Entropy. 27(9). 992–992.
2.
Ferraro, Stefano, et al.. (2025). FOCUS: object-centric world models for robotic manipulation. Frontiers in Neurorobotics. 19. 1585386–1585386. 1 indexed citations
3.
Friston, Karl, Conor Heins, Tim Verbelen, et al.. (2025). From pixels to planning: scale-free active inference. PubMed. 5. 1521963–1521963. 4 indexed citations
4.
Friston, Karl, Lancelot Da Costa, Alexander Tschantz, et al.. (2024). Supervised structure learning. Biological Psychology. 193. 108891–108891. 12 indexed citations
5.
Verbelen, Tim, et al.. (2024). Object-Centric Scene Representations Using Active Inference. Neural Computation. 36(4). 677–704. 2 indexed citations
6.
Verbelen, Tim, et al.. (2024). Learning dynamic cognitive map with autonomous navigation. Frontiers in Computational Neuroscience. 18. 1498160–1498160. 1 indexed citations
7.
Verbelen, Tim, et al.. (2024). Spatial and Temporal Hierarchy for Autonomous Navigation Using Active Inference in Minigrid Environment. Entropy. 26(1). 83–83. 3 indexed citations
8.
Friston, Karl, Thomas Parr, Conor Heins, et al.. (2023). Federated inference and belief sharing. Neuroscience & Biobehavioral Reviews. 156. 105500–105500. 13 indexed citations
9.
Verbelen, Tim, et al.. (2023). Dermatologist versus artificial intelligence confidence in dermoscopy diagnosis: Complementary information that may affect decision‐making. Experimental Dermatology. 32(10). 1744–1751. 3 indexed citations
10.
Brochez, Liève, Tim Verbelen, Cedric De Boom, et al.. (2022). The value of measuring uncertainty in neural networks in dermoscopy. Journal of the American Academy of Dermatology. 87(5). 1191–1193. 2 indexed citations
11.
12.
Verbelen, Tim, et al.. (2022). Embodied Object Representation Learning and Recognition. Frontiers in Neurorobotics. 16. 840658–840658. 7 indexed citations
13.
Verbelen, Tim, et al.. (2021). Active Vision for Robot Manipulators Using the Free Energy Principle. Frontiers in Neurorobotics. 15. 642780–642780. 14 indexed citations
14.
Boom, Cedric De, et al.. (2021). Dynamic Narrowing of VAE Bottlenecks Using GECO and L0 Regularization. 1–8. 2 indexed citations
15.
Boom, Cedric De, et al.. (2020). Learning Generative State Space Models for Active Inference. Frontiers in Computational Neuroscience. 14. 574372–574372. 20 indexed citations
16.
Verbelen, Tim, et al.. (2019). Bayesian policy selection using active inference. Ghent University Academic Bibliography (Ghent University). 3 indexed citations
17.
Leroux, Sam, Steven Bohez, Bert Vankeirsbilck, et al.. (2019). Multi-fidelity deep neural networks for adaptive inference in the internet of multimedia things. Future Generation Computer Systems. 97. 355–360. 10 indexed citations
18.
Bohez, Steven, Tim Verbelen, Sam Leroux, et al.. (2018). Robot navigation using a variational dynamics model for state estimation and robust control. Ghent University Academic Bibliography (Ghent University). 1 indexed citations
19.
Vankeirsbilck, Bert, Tim Verbelen, Nicolas Staelens, et al.. (2013). Quality of experience driven control of interactive media stream parameters. Ghent University Academic Bibliography (Ghent University). 1282–1287. 4 indexed citations
20.
Verbelen, Tim, Pieter Simoens, Filip De Turck, & Bart Dhoedt. (2013). Leveraging Cloudlets for Immersive Collaborative Applications. IEEE Pervasive Computing. 12(4). 30–38. 55 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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