ESAT
Kasteelpark Arenberg 10, bus 2446, B-3001 Leuven, Belgium
office: B00.16
phone: 2 18 02 fax: 2 19 70
email: .@esat.kuleuven.be
www: Personal homepage
2018-2024:
--------------------------------------------------------------------------------------------------------- 2012-2017:
--------------------------------------------------------------------------------------------------------- Interdisciplinary research with emphasis on the theory and applications of: - Support vector machines and kernel-based learning - Data-driven modelling and machine learning - Neural networks and deep learning - Systems, modelling and control - Complex networks - Optimization - Nonlinear circuits and systems - Nonlinear signal processing.
--------------------------------------------------------------------------------------------------------- AI @ KU Leuven:
---------------------------------------------------------------------------------------------------------- Invited talksIEEE Neural Networks Pioneer Award Keynote talk: "Least Squares Support Vector Machines and Deep Learning", IEEE World Congress on Computational Intelligence WCCI - IJCNN 2024, Yokohama Japan, July 2024. "Neural networks and kernel machines: the best of both worlds": invited lecture at AIDD Third School (Leuven, Oct 2022) Advanced machine learning for Innovative Drug Discovery [pdf] "Deep learning and Kernel Machines": keynote talk at AIAI/EANN 2021 conference (17th International Conference on Artificial Intelligence Applications and Innovations and 22nd International Conference on Engineering Applications of Neural Networks), June 25-27 2021, June 2021 [pdf] "Kernel spectral clustering and networks applications": keynote talk at 2020 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, The Hague, Netherlands, 7-10 Dec 2020, Dec 2020 [pdf] "Deep Learning and Kernel Machines: a Unifying Picture": plenary talk at Second Symposium on Machine Learning and Dynamical Systems, The Fields Institute, Toronto, Sept 2020 [pdf] "Deep Learning, Neural Networks and Kernel Machines: new synergies": keynote talk at IEEE World Congress on Computational Intelligence (WCCI-IJCNN 2020), Glasgow July 2020 [pdf] "Deep Learning and Kernel Machines": invited talk at Visum summer school, Porto, July 2020 [pdf] "Generative Restricted Kernel Machines: towards fully explainable deep learning": talk at Data Science Meetup LLN, Dec 2019 [pdf] "Deep Learning, Neural Networks and Kernel Machines: towards a unifying framework": invited AI Seminar at BeCentral Brussels, Oct 2019 [pdf] "Deep Learning, Neural Networks and Kernel Machines": invited lecture series at DeepLearn 2019 International Summer School, Warsaw July 2019: "Future Data-driven Modelling": keynote talk at 26th International Workshop on Intelligent Computing in Engineering (EG-ICE 2019), Leuven, July 2019 [pdf] "Deep Learning and Kernel Machines: towards a Unifying Framework": plenary lecture at CIARP 2018, Madrid, Nov 2018 [pdf] "Deep Learning and Kernel Machines": invited lecture series at DeepLearn 2018 International Summer School, Genova July 2018: "Function Estimation, Model Representations and Nonlinear System Identification": keynote talk at Workshop Nonlinear System Identification Benchmarks, Liege April 2018 [pdf] "Deep Restricted Kernel Machines": - talk at Leuven Statistics Days, April 2019 [pdf] "Learning with primal and dual model representations: new extensions": invited talk at MFO Oberwolfach 2016, Workshop on Learning Theory and Approximation: [pdf] "Learning with primal and dual model representations: a unifying picture": plenary talk ICASSP 2016, Shanghai: [pdf][youtube] "SVD meets LS-SVM: a unifying picture": invited seminar at UCL, LLN 2015: [pdf] "Learning with primal and dual model representations": invited lecture at CIMI Workshop, Toulouse 2015: [pdf]
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![[logo]](https://www.esat.kuleuven.be/sista/members/ERC_logo.jpg){kind=logo}
Current research team:
| Sonny Achten, Yingyi Chen, Bram De Cooman, Henri De Plaen, Alex Lambert, Zander Op de Beeck, Qinghua Tao, Meixi Wang, David Winant, Xinjie Zeng |
Johan A.K. Suykens was born in Willebroek Belgium, May 18 1966. He received the master degree in Electro-Mechanical Engineering and the PhD degree in Applied Sciences from the Katholieke Universiteit Leuven, in 1989 and 1995, respectively. In 1996 he has been a Visiting Postdoctoral Researcher at the University of California, Berkeley. He has been a Postdoctoral Researcher with the Fund for Scientific Research FWO Flanders and is currently a full Professor with KU Leuven. He is author of the books "Artificial Neural Networks for Modelling and Control of Non-linear Systems" (Kluwer Academic Publishers) and "Least Squares Support Vector Machines" (World Scientific), co-author of the book "Cellular Neural Networks, Multi-Scroll Chaos and Synchronization" (World Scientific) and editor of the books "Nonlinear Modeling: Advanced Black-Box Techniques" (Kluwer Academic Publishers), "Advances in Learning Theory: Methods, Models and Applications" (IOS Press) and "Regularization, Optimization, Kernels, and Support Vector Machines" (Chapman & Hall/CRC). In 1998 he organized an International Workshop on Nonlinear Modelling with Time-series Prediction Competition. He has served as associate editor for the IEEE Transactions on Circuits and Systems (1997-1999 and 2004-2007), the IEEE Transactions on Neural Networks (1998-2009), the IEEE Transactions on Neural Networks and Learning Systems (from 2017) and the IEEE Transactions on Artificial Intelligence (from April 2020). He received an IEEE Signal Processing Society 1999 Best Paper Award, a 2019 Entropy Best Paper Award and several Best Paper Awards at International Conferences. He is a recipient of the International Neural Networks Society INNS 2000 Young Investigator Award for significant contributions in the field of neural networks. He has been awarded the 2024 IEEE Neural Networks Pioneer Award. He has served as a Director and Organizer of the NATO Advanced Study Institute on Learning Theory and Practice (Leuven 2002), as a program co-chair for the International Joint Conference on Neural Networks 2004 and the International Symposium on Nonlinear Theory and its Applications 2005, as an organizer of the International Symposium on Synchronization in Complex Networks 2007, a co-organizer of the NIPS 2010 workshop on Tensors, Kernels and Machine Learning, and chair of ROKS 2013 and DEEPK 2024 International Workshop on Deep Learning and Kernel Machines. He has been awarded an ERC Advanced Grant 2011 and 2017, has been elevated IEEE Fellow 2015 for developing least squares support vector machines, and is ELLIS Fellow. He is currently serving as program director of Master AI at KU Leuven. ---------------------------------------------------------------------------------------------------------------------- Books and edited books
J.A.K. Suykens, J.P.L. Vandewalle, B.L.R. De Moor, Artificial Neural Networks for Modeling and Control of Non-Linear Systems, Springer, 1996 (ISBN 0792396782) [more information]J.A.K. Suykens, T. Van Gestel, J. De Brabanter, B. De Moor, J. Vandewalle, Least Squares Support Vector Machines, World Scientific, Singapore, 2002 (ISBN 981-238-151-1) [more information]M.E. Yalcin, J.A.K. Suykens, J.P.L. Vandewalle, Cellular Neural Networks, Multi-Scroll Chaos and Synchronization, World Scientific Series on Nonlinear Science, Series A - Vol. 50, Singapore, 2005 (ISBN 981-256-161-7) [more information]J.A.K. Suykens, J.P.L. Vandewalle (Eds.) Nonlinear Modeling : Advanced Black-Box Techniques, Springer, 1998 (ISBN 0792381955) [more information]J.A.K. Suykens, G. Horvath, S. Basu, C. Micchelli, J. Vandewalle (Eds.) Advances in Learning Theory: Methods, Models and Applications, NATO Science Series III: Computer & Systems Sciences, Volume 190, IOS Press Amsterdam, 2003, 436pp. (ISBN: 1 58603 341 7) [more information]J.A.K. Suykens, M. Signoretto, A. Argyriou (Eds.) Regularization, Optimization, Kernels, and Support Vector Machines, Chapman & Hall/CRC, Machine Learning & Pattern Recognition Series, Boca Raton US, 2014, 525 pp (ISBN 9781482241396) [more information]------------------------------------------------------------------------------------------------------------------------- Publications: Complete List
Publications: Support vector machines and kernel-based learningPublications: Deep learning, neural networksPublications: Robustness & AIPublications: Explainability & AIPublications: Chaos, synchronization, complex networksPublications: Systems and control, nonlinear signal processingPublications: Biomedical applications and bioinformaticsPublications: OptimizationPublications: Quantum mechanics
Publications at Google Scholar
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- Tensor Tools for Taming the Curse
- Rethinking Transformers Through Duality Principles
- E-DUALITY - Exploring Duality for Future Data-driven Modelling
- FAIR 2-0 - AI Research Program
- 2024 IEEE CIS Neural Networks Pioneer Award
Johan Suykens has been awarded the prestigious 2024 IEEE CIS Neural Networks Pioneer Award, for contributions to least squares support vector machines.
This award recognizes significant contributions to early concepts and sustained developments in the field of Neural Networks https://cis.ieee.org/awards/ieeecis-awards.
Past Recipients are listed here https://cis.ieee.org/awards/past-recipients#NeuralNetworksPioneerAward and include e.g. Bernard Widrow (1991), Shun-Ichi Amari (1992), Geoffrey Hinton (1998), Leon Chua (2000), Vladimir Vapnik (2010), Yann LeCun (2014), Juergen Schmidhuber (2016), Yoshua Bengio (2019) and others.
- The 2024 IEEE CIS Neural Networks Pioneer Award
For contributions to least squares support vector machines
- Johan Suykens has been elected ELLIS Fellow
Johan Suykens has been elected ELLIS Fellow in the ELLIS (European Laboratory for Learning and Intelligent Systems) unit Leuven.
- 2019 Entropy Best Paper Award
Johan Suykens together with Zahra Karevan have received a 2019 Entropy Best Paper Award for the paper "Transductive Feature Selection Using Clustering-Based Sample Entropy for Temperature Prediction in Weather Forecasting" (Entropy 2018, 20(4), 264; https://doi.org/10.3390/e20040264).
- "Gouden krijtje" award "Best Prof" in Mathematical Engineering 2018-2019
- ERC Advanced Grant 2017 E-DUALITY
- Fellow IEEE (2015)
- VUB Leerstoel for the academic year 2012-2013 granted to Prof. Johan Suykens (KU Leuven, ESAT-SCD-SISTA-SMC/IBBT Future Health Department)
Topic: “Data-driven modelling: an integrative approach”
Registration: email to anna.marconato@vub.ac.be before Wednesday 26th September 2012
Venue: VUB Etterbeek
Date: October- First inaugural lecture on Wednesday 3rd October 2012, from 16:00 to 17:00 in the Promotiezaal “Aloïs Gerlo” of the VUB-Etterbeek (building D – D.2.01)
Program: See PDF - ERC Advanced Grant 2011
- International Neural Networks Society INNS 2000 Young Investigator Award
- IEEE Signal Processing Society 1999 Best Paper Award (Senior award)
- Associate Editor IEEE Transactions on Artificial Intelligence
- Associate Editor IEEE Transactions on Neural Networks and Learning Systems
- E-Reference Signal Processing: Section Editor Machine Learning
- Associate Editor IEEE Transactions on Circuits and Systems - Express Briefs (2004-2007)
- Associate Editor IEEE Transactions on Neural Networks (1998-2009)
- Associate Editor IEEE Transactions on Circuits and Systems-I (Fundamental Theory and Applications) (1997-1999)
- Associate Editor IEEE Circuits and Systems Magazine (2010-2011)
- Guest associate editor International Journal of Bifurcation and Chaos (2010-2011)
- Technical committee member IEEE Neural Networks
- TI genootschap BIRA bestuurslid
- Technical committee member IEEE Signal Processing Society Machine Learning for Signal Processing
- Technical committee member IEEE Circuits & Systems Society Nonlinear Circuits and Systems
- Technical committee member IEEE Signal Processing Society Neural Networks for Signal Processing
- Technical committee member IEEE Circuits & Systems Society Cellular Neural Networks and Array Computing
- invited speaker for the workshop of IEEE Computational Intelligence Society on Grand challenges of computational intelligence.
View the recorded presentations on YouTube:
- Invited talks KVCV-BCS 2010, SYNCLINE 2010, ICCHA 2011, IEEE-CIS Grand Challenges 2012, VUB Leerstoel 2012, RANSO2013, NOLTA 2014, ICLA 2014, BigDat 2015, Statlearn 2015, CIMI 2015, ICASSP 2016, MFO 2016, Nonlinear Sysid Benchmarks 2018, DeepLearn 2018, CIARP 2018, EG-ICE 2019, DeepLearn 2019, VISUM 2020, ICORS 2020, WCCI-IJCNN 2020
- Invited talks before 2010: NDES 1999, PASE 2000, IEEE-IMTC 2001, IJCNN 2001, ICRM 2002, FOCM 2002, VOC 2005, STATUA 2006, SCCB 2006, CCKM06, ASCI 2007, ICCHA 2007, MFO 2008, BOMM08, SYSID 2009
- Tutorial speaker IJCNN 2000, IJCNN 2003, IJCNN 2005, ICANN 2007, WCCI 2010
- Chairman and programme director of Master of Artificial Intelligence Programme K.U. Leuven (2004-2008 and Aug 2017- now)
- IEEE Computational Intelligence Society Benelux Chapter
- Program co-chair International Joint Conference on Neural Networks (IJCNN 2004)
- Director NATO Advanced Study Institute on Learning Theory and Practice 2002
- Minicourse speaker ECC 2001
- Program co-chair International Symposium on Nonlinear Theory and its Applications (NOLTA 2005)
- Co-chair International Symposium on Synchronization in Complex Networks (SynCoNet 2007)
- co-organizer NIPS 2010 Workshop on Tensors, Kernels and Machine Learning (TKML 2010)