Johan A. K. Suykens
- Computational Mathematics top 0.2%
- Computer Vision and Pattern Recognition top 0.05%
- Face and Expression Recognition 96
- Artificial Intelligence top 0.02%
- Neural Networks and Applications 128
- Control and Systems Engineering top 0.05%
- Control Systems and Identification 80
- Fault Detection and Control Systems 64
- Statistical and Nonlinear Physics top 0.1%
- Chaos control and synchronization 32
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- Sparse and Compressive Sensing Techniques 60
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- Blind Source Separation Techniques 35
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- Nonlinear Dynamics and Pattern Formation 35
- Co-authors
- Joos VandewalleBart De MoorTony Van GestelJos De BrabanterMüştak E. YalçınKristiaan PelckmansSabine Van HuffelXiaolin Huang
- Journals
- Bioinformatics (3 papers)PLoS ONE (7 papers)IEEE Transactions on Pattern Analysis and Machine Intelligence (7 papers)
- Partner nations
- BelgiumChinaUnited States
In The Last Decade
Johan A. K. Suykens
531 papers receiving 29.3k citations
Hit Papers
Peers
Comparison fields: 5 of 224
- Computational Mathematics 408
- Computer Vision and Pattern Recognition 6.2k
- Artificial Intelligence 9.6k
- Control and Systems Engineering 6.4k
- Statistical and Nonlinear Physics 3.1k
Countries citing papers authored by Johan A. K. Suykens
This map shows the geographic impact of Johan A. K. Suykens'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 Johan A. K. Suykens with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Johan A. K. Suykens more than expected).
Fields of papers citing papers by Johan A. K. Suykens
This network shows the impact of papers produced by Johan A. K. Suykens. 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 Johan A. K. Suykens. The network helps show where Johan A. K. Suykens may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Johan A. K. Suykens, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 5 | |
| 2 | 2024 | 4 | |
| 3 | 2024 | 8 | |
| 4 | 2021 | 63 | |
| 5 | 2020 | 2 | |
| 6 | Learning from partially labeled data. | 2020 | 0 |
| 7 | An SVD-free Approach to a Class of Structured Low Rank Matrix Optimization Problems with Application to System Identification | 2013 | 23 |
| 8 | 2011 | 42 | |
| 9 | On Robustness in Kernel Based Regression | 2010 | 2 |
| 10 | Transductive Rademacher Complexities for Learning over a Graph | 2007 | 1 |
| 11 | A Risk Minimization Principle for a Class of Parzen Estimators | 2007 | 13 |
| 12 | Electric Load Forecasting: Using Kernel-Based Modeling for Nonlinear System Identification | 2007 | 37 |
| 13 | Automated detection of a preseizure state: non-linear EEG analysis in epilepsy by Cellular Nonlinear Networks and Volterra systems: Research Articles | 2006 | 2 |
| 14 | Ensemble Learning of Coupled Parmeterised Kernel Models | 2003 | 6 |
| 15 | Advances in learning theory : methods, models and applications | 2003 | 80 |
| 16 | Sparse least squares Support Vector Machine classifiers. | 2000 | 100 |
| 17 | Least squares support vector machine classifiers: a large scale algorithm | 1999 | 192 |
| 18 | 1998 | 104 | |
| 19 | Quasi-linear approach to nonlinear-systems and the design of n-double scroll (n = 1, 2, 3, 4, ...) | 1991 | 14 |
| 20 | MUNIN:an expert EMG assistant | 1988 | 26 |
About Johan A. K. Suykens
Johan A. K. Suykens is a scholar working on Computational Mathematics, Artificial Intelligence and Statistical and Nonlinear Physics, having authored 543 papers that have together received 30.7k indexed citations. Recurring topics across this work include Neural Networks and Applications (128 papers), Face and Expression Recognition (96 papers), Control Systems and Identification (80 papers), Fault Detection and Control Systems (64 papers), Sparse and Compressive Sensing Techniques (60 papers), Blind Source Separation Techniques (35 papers), Nonlinear Dynamics and Pattern Formation (35 papers) and Chaos control and synchronization (32 papers). The work is most often cited by research in Computational Mathematics (408 citations), Computer Vision and Pattern Recognition (6.2k citations) and Artificial Intelligence (9.6k citations). Johan A. K. Suykens has collaborated with scholars based in Belgium, China and United States. Frequent co-authors include Joos Vandewalle, Bart De Moor, Tony Van Gestel, Jos De Brabanter, Müştak E. Yalçın, Kristiaan Pelckmans, Sabine Van Huffel, Xiaolin Huang, Carlos Alzate and Leon O. Chua. Their work appears in journals such as Bioinformatics, PLoS ONE and IEEE Transactions on Pattern Analysis and Machine Intelligence.
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.