Bioinformatics and AI seminar series

Johan A. K. Suykens was born in Willebroek, Belgium, 18 May 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 served as a Director and Organizer of the NATO Advanced Study Institute on Learning Theory and Practice (Leuven 2002), as a programme 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. 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 programme director of Master AI at KU Leuven.

I am a Research Data Manager part of the Digital Competence Center and the Library Research Data and Software Services at TU Delft.
I started my scientific training as a biomedical researcher having mostly biochemistry projects. As my research interests grew, they became more and more data intensive so I earned a PhD in bioinformatics and systems Biology.
I am very aware of the steady increase of data generation and (re)use by researchers creating data-related bottlenecks. As part of my job, I aim to help researchers, both established and still undergoing training, to deal with their specific data bottlenecks: management, analysis, visualisation, and so on.

Most of my work was done with data obtained from microorganisms like brewing/baking yeast, some other fungi and microorganisms in general.

I am a postdoctoral researcher at VIB/KU-Leuven. My research focuses on development of computational and AI solutions for studying gene regulation in single cell and spatial multi-omics analysis and integration.

Francesco Tonin is currently a post-doctoral researcher with the Laboratory for Information and Inference Systems at the École Polytechnique Fédérale de Lausanne (EPFL), Switzerland. He obtained his master’s degree in Computer Science from KU Leuven, Belgium in 2019. Sequentially, he pursued a PhD degree at KU Leuven under the supervision of Prof. Johan Suykens and Prof. Panos Patrinos.

Giovanni Samaey is toegepast wiskundige en computerwetenschapper. Hij ontwikkelt en onderzoekt algoritmes om computersimulaties vele malen te versnellen. Vele belangrijke problemen, zoals kanker, verkeer en slimme materialen, hebben met elkaar gemeen dat microscopische effecten (zoals het gedrag van individuele cellen of voertuigen) het gedrag op macroscopische schaal (de tumor of de verkeersstroom) beïnvloeden. Giovanni bestudeert algoritmes om in dergelijke gevallen tot aanvaardbare rekentijden te komen. Dit onderzoek combineert aspecten van toegepaste wiskunde en computerwetenschappen, en nodigt uit tot interactie met tal van wetenschappelijke domeinen.

Passionate about biology and data science, I would describe myself as a polyvalent scientist schooled to master a broad range of biotechnological tools as well as applying cutting edge statistical methods to data.