Johan Suykens received his 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 and director of Master AI at 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).
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 an ERC Advanced Grant 2011 and 2017, and has been elevated IEEE Fellow 2015 for developing least squares support vector machines. Since 2017, he has served as associate editor for the IEEE Transactions on Neural Networks and Learning Systems.
At VISUM 2020, Professor Dr. Johan Suykens will speak on “Deep Learning and Kernel Machines”.