Joos Vandewalle

44.7k total citations · 10 hit papers
560 papers, 31.0k citations indexed

About

Joos Vandewalle is a scholar working on Artificial Intelligence, Control and Systems Engineering and Signal Processing. According to data from OpenAlex, Joos Vandewalle has authored 560 papers receiving a total of 31.0k indexed citations (citations by other indexed papers that have themselves been cited), including 195 papers in Artificial Intelligence, 105 papers in Control and Systems Engineering and 105 papers in Signal Processing. Recurrent topics in Joos Vandewalle's work include Neural Networks and Applications (116 papers), Blind Source Separation Techniques (68 papers) and Control Systems and Identification (48 papers). Joos Vandewalle is often cited by papers focused on Neural Networks and Applications (116 papers), Blind Source Separation Techniques (68 papers) and Control Systems and Identification (48 papers). Joos Vandewalle collaborates with scholars based in Belgium, United States and Singapore. Joos Vandewalle's co-authors include Johan A. K. Suykens, Bart De Moor, Lieven De Lathauwer, Jos De Brabanter, Tony Van Gestel, Sabine Van Huffel, Müştak E. Yalçın, George W. Fisher, Marc Moonen and Bart Preneel and has published in prestigious journals such as The Lancet, Journal of the American Statistical Association and PLoS ONE.

In The Last Decade

Joos Vandewalle

511 papers receiving 29.1k citations

Hit Papers

Least Squares Support Vector Machine Classifiers 1991 2026 2002 2014 1999 2002 2000 2000 2002 2.0k 4.0k 6.0k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Joos Vandewalle Belgium 64 8.1k 5.9k 5.6k 4.0k 3.5k 560 31.0k
Gene H. Golub United States 84 4.7k 0.6× 5.8k 1.0× 3.6k 0.6× 3.5k 0.9× 5.1k 1.5× 294 45.6k
Bart De Moor Belgium 74 7.0k 0.9× 3.6k 0.6× 9.0k 1.6× 2.8k 0.7× 2.3k 0.7× 641 30.8k
Johan A. K. Suykens Belgium 71 9.6k 1.2× 6.2k 1.0× 6.4k 1.2× 2.2k 0.6× 3.2k 0.9× 543 30.7k
Шун-ичи Амари Japan 69 9.8k 1.2× 3.5k 0.6× 1.7k 0.3× 8.6k 2.1× 1.8k 0.5× 314 24.6k
Jorge Nocedal United States 44 6.1k 0.7× 3.9k 0.7× 4.4k 0.8× 1.1k 0.3× 3.6k 1.0× 105 37.3k
Jieping Ye United States 87 7.9k 1.0× 8.7k 1.5× 1.5k 0.3× 2.3k 0.6× 1.7k 0.5× 439 25.3k
Chih‐Jen Lin Taiwan 54 18.7k 2.3× 16.3k 2.8× 3.0k 0.5× 4.9k 1.2× 3.8k 1.1× 145 51.7k
Alex Smola United States 53 17.1k 2.1× 8.9k 1.5× 3.8k 0.7× 3.3k 0.8× 3.0k 0.9× 121 37.5k
Benjamin Recht United States 47 4.8k 0.6× 5.0k 0.8× 1.0k 0.2× 2.6k 0.6× 1.6k 0.4× 101 16.5k
Qiang Yang Hong Kong 98 32.1k 3.9× 13.7k 2.3× 2.8k 0.5× 4.7k 1.2× 6.2k 1.8× 860 62.9k

Countries citing papers authored by Joos Vandewalle

Since Specialization
Citations

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

Fields of papers citing papers by Joos Vandewalle

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Joos Vandewalle

This figure shows the co-authorship network connecting the top 25 collaborators of Joos Vandewalle. A scholar is included among the top collaborators of Joos Vandewalle 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 Joos Vandewalle. Joos Vandewalle 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.
Suykens, Johan A. K., Andreas A. Argyriou, Kris De Brabanter, et al.. (2013). International workshop on advances in regularization, optimization, kernel methods and support vector machines : theory and applications (ROKS 2013). Lirias (KU Leuven). 1–128. 1 indexed citations
2.
Tranchevent, Léon-Charles, et al.. (2012). Visualizing high dimensional datasets using parallel coordinaties : application to gene prioritization. International Conference on Bioinformatics. 52–57. 1 indexed citations
3.
Batselier, Kim, Philippe Dreesen, Marco Signoretto, et al.. (2012). Joint Regression and Linear Combination of Time Series for Optimal Prediction. The European Symposium on Artificial Neural Networks.
4.
Antal, Péter, et al.. (2000). Incorporation of Prior Knowledge in Black-box Models : Comparison of Transformation Methods from Bayesian Network to Multilayer Perceptrons. Uncertainty in Artificial Intelligence. 7–12. 2 indexed citations
5.
Vandewalle, Joos, et al.. (1999). Diffusion analysis of Feistel networks. 11(3). 101–108.
6.
Suykens, Johan A. K., et al.. (1999). Least squares support vector machine classifiers: a large scale algorithm. Digital Access to Libraries (Université catholique de Louvain (UCL), l'Université de Namur (UNamur) and the Université Saint-Louis (USL-B)). 839–842. 192 indexed citations
7.
Espinosa, Jairo & Joos Vandewalle. (1998). Predictive Control Using Fuzzy Models Applied to a Steam Generating Unit. 3(4). 151–160. 16 indexed citations
8.
Moreau, Yves & Joos Vandewalle. (1997). Composition methods for the integration of dynamical neural networks. The European Symposium on Artificial Neural Networks. 121(11 Suppl). 303–308.
9.
Verrelst, Herman, Yves Moreau, Joos Vandewalle, & D. Timmerman. (1997). Use of a Multi-Layer Perceptron to Predict Malignancy in Ovarian Tumors. Neural Information Processing Systems. 10. 978–984. 4 indexed citations
10.
Moreau, Yves & Joos Vandewalle. (1997). Equivalence between dynamic one-hidden-layer perceptrons and dynamic perceptrons without hidden layer. 6.
11.
Daemen, Joan, René Govaerts, & Joos Vandewalle. (1993). Cryptanalysis of MUX-LFSR based scramblers. Frontiers in Immunology. 12. 55–61. 2 indexed citations
12.
Suykens, Johan A. K., Bart De Moor, & Joos Vandewalle. (1993). Stabilizing neural controllers: a case study for swinging up a double inverted pendulum. PLoS ONE. 10(5). 411–414. 1 indexed citations
13.
Bosselaers, Antoon, Jason Brandt, David Chaum, et al.. (1993). RIPE integrity primitives Part II Final report of RACE 1040. Department of Computer Science [CS]. 2–118. 1 indexed citations
14.
Vandenberghe, Lieven & Joos Vandewalle. (1991). The computation of equilibrium points in cellular neural networks using complementary pivoting. 30–38. 3 indexed citations
15.
Vandewalle, Joos, et al.. (1991). A new approach to the design of discrete Hopfield associative memory. 1705–1710. 1 indexed citations
16.
Moor, Bart De & Joos Vandewalle. (1987). All nonnegative solutions of sets of linear equations and the linear complementarity problem. International Symposium on Circuits and Systems. 1076–1079. 4 indexed citations
17.
Goossens, Gert, Jan M. Rabaey, Joos Vandewalle, & Hugo De Man. (1987). An efficient microcode compiler for custom multiprocessor DSP-systems. International Conference on Computer Aided Design. 24–27. 7 indexed citations
18.
Huffel, Sabine Van, et al.. (1984). The total linear least squares problem: formulation, algorithm and applications. International Symposium on Circuits and Systems. 328–331. 3 indexed citations
19.
Vandewalle, Joos, Hugo De Man, & Jan M. Rabaey. (1982). A pictorial derivation of the signal processing mechanism of multiphase switched capacitor networks. International Symposium on Circuits and Systems. 25–28. 4 indexed citations
20.
Man, H. De, Jan M. Rabaey, Luc Claesen, & Joos Vandewalle. (1981). DIANA-SC : A Complete CAD system for switched capacitor filters. European Solid-State Circuits Conference. 130–133. 6 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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