Arnout Van Messem

472 total citations
22 papers, 239 citations indexed

About

Arnout Van Messem is a scholar working on Molecular Biology, Artificial Intelligence and Statistics and Probability. According to data from OpenAlex, Arnout Van Messem has authored 22 papers receiving a total of 239 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 6 papers in Artificial Intelligence and 4 papers in Statistics and Probability. Recurrent topics in Arnout Van Messem's work include Gene Regulatory Network Analysis (3 papers), Advanced Statistical Methods and Models (3 papers) and Statistical Methods and Inference (3 papers). Arnout Van Messem is often cited by papers focused on Gene Regulatory Network Analysis (3 papers), Advanced Statistical Methods and Models (3 papers) and Statistical Methods and Inference (3 papers). Arnout Van Messem collaborates with scholars based in Belgium, South Korea and Germany. Arnout Van Messem's co-authors include Andreas Christmann, Wesley De Neve, Joris Vankerschaver, Patrick L.S. van Dun, Mioara Alina Nicolaie, Stephen Depuydt, Ingo Steinwart, Hyunjin Shim, Tanja Ćirković Veličković and Shodhan Rao and has published in prestigious journals such as PLoS ONE, BMC Bioinformatics and Machine Learning.

In The Last Decade

Arnout Van Messem

20 papers receiving 228 citations

Peers

Arnout Van Messem

CVPR

Abel Folch‐Fortuny Spain

Mohamed A. El-Sayed Egypt

David Haws United States

Mauricio Araya Chile

Shuichi Kurogi Japan

Jakramate Bootkrajang Thailand

Louis Ferré France

Edwin R. Arboleda Philippines

Miguel De‐la‐Torre Mexico

Abel Folch‐Fortuny Spain

Arnout Van Messem

30 ×0.6

15 ×0.4

CVPR

100 ×2.6

34 ×0.9

54 ×1.5

Citations per year, relative to Arnout Van Messem Arnout Van Messem (= 1×) peers Abel Folch‐Fortuny

Countries citing papers authored by Arnout Van Messem

Since Specialization

Citations

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

Fields of papers citing papers by Arnout Van Messem

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Arnout Van Messem. 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 Arnout Van Messem. The network helps show where Arnout Van Messem may publish in the future.

Co-authorship network of co-authors of Arnout Van Messem

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

All Works

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20 of 20 papers shown

Wang, Haohan, et al.. (2025). Re-assessing accuracy degradation: a framework for understanding DNN behavior on similar-but-non-identical test datasets. Machine Learning. 114(3). 1 indexed citations

Messem, Arnout Van, et al.. (2024). Interpreting Stress Detection Models Using SHAP and Attention for MuSe-Stress 2022. IEEE Transactions on Affective Computing. 16(2). 1031–1043. 2 indexed citations

Mohammed, Mohammed Aliy, Janarthanan Krishnamoorthy, Sofie Van Hoecke, et al.. (2023). Tryp: a dataset of microscopy images of unstained thick blood smears for trypanosome detection. Scientific Data. 10(1). 716–716. 4 indexed citations

Vankerschaver, Joris, et al.. (2023). How to make sense of 3D representations for plant phenotyping: a compendium of processing and analysis techniques. Plant Methods. 19(1). 60–60. 44 indexed citations

Vankerschaver, Joris, et al.. (2023). CRISPR-Cas-Docker: web-based in silico docking and machine learning-based classification of crRNAs with Cas proteins. BMC Bioinformatics. 24(1). 167–167. 1 indexed citations

Messem, Arnout Van, et al.. (2023). MuSe-Personalization 2023: Feature Engineering, Hyperparameter Optimization, and Transformer-Encoder Re-discovery. Ghent University Academic Bibliography (Ghent University). 89–97. 3 indexed citations

Veličković, Tanja Ćirković, et al.. (2022). MP-Net: Deep learning-based segmentation for fluorescence microscopy images of microplastics isolated from clams. PLoS ONE. 17(6). e0269449–e0269449. 19 indexed citations

Vankerschaver, Joris, et al.. (2022). In silico optimization of RNA–protein interactions for CRISPR-Cas13-based antimicrobials. Biology Direct. 17(1). 27–27. 11 indexed citations

Vankerschaver, Joris, et al.. (2022). Rethinking Protein Drug Design with Highly Accurate Structure Prediction of Anti-CRISPR Proteins. Pharmaceuticals. 15(3). 310–310. 17 indexed citations

10.

Kang, Hanul, et al.. (2021). Towards a quantitative analysis of class activation mapping for deep learning-based computer-aided diagnosis. Ghent University Academic Bibliography (Ghent University). 20–20. 7 indexed citations

11.

Messem, Arnout Van, et al.. (2021). Parameter estimation for models of chemical reaction networks from experimental data of reaction rates. International Journal of Control. 96(2). 392–407. 1 indexed citations

12.

Messem, Arnout Van, et al.. (2020). An Automated Model Reduction Method for Biochemical Reaction Networks. Symmetry. 12(8). 1321–1321. 5 indexed citations

13.

Messem, Arnout Van, et al.. (2020). Item Measurement for Logistics-Oriented Belt Conveyor Systems Using a Scenario-Driven Approach and Automata-Based Control Design. Ghent University Academic Bibliography (Ghent University). 66. 271–280. 2 indexed citations

14.

Neve, Wesley De, et al.. (2020). Perturbation analysis of gradient-based adversarial attacks. Pattern Recognition Letters. 135. 313–320. 8 indexed citations

15.

Vandersmissen, Baptist, et al.. (2020). Investigating the significance of adversarial attacks and their relation to interpretability for radar-based human activity recognition systems. Computer Vision and Image Understanding. 202. 103111–103111. 13 indexed citations

16.

Messem, Arnout Van, et al.. (2019). Box-Scan: An Efficient and Effective Algorithm for Box Dimension Measurement in Conveyor Systems using a Single RGB-D Camera. Ghent University Academic Bibliography (Ghent University). 160–167. 7 indexed citations

17.

Messem, Arnout Van, et al.. (2018). A Novel Technique for Model Reduction of Biochemical Reaction Networks. IFAC-PapersOnLine. 51(19). 28–31. 3 indexed citations

18.

Christmann, Andreas, Ingo Steinwart, & Arnout Van Messem. (2009). On consistency and robustness properties of support vector machines for heavy-tailed distributions. Statistics and Its Interface. 2(3). 311–327. 28 indexed citations

19.

Christmann, Andreas & Arnout Van Messem. (2008). Bouligand Derivatives and Robustness of Support Vector Machines for Regression. Journal of Machine Learning Research. 9(30). 915–936. 28 indexed citations

20.

Messem, Arnout Van. (2007). Bouligand derivatives and robustness of support vector machines. Open Repository and Bibliography (University of Liège).

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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