Curriculum Vitae
Bio
Marcel van Gerven (‘s-Hertogenbosch, 1976) was trained as a cognitive scientist. He received his degree in Cognitive Science in 2000 at Radboud University. After completing his studies, he worked at the Max Planck Institute for Psycholinguistics and the Institute of Ophthalmology, UCL, London. He also worked in the software industry on artificial intelligence (AI) and educational applications. In 2007 he obtained his PhD at Radboud University on probabilistic models for cancer diagnosis, prognosis and treatment selection. This research was done in collaboration with clinicians at the Netherlands Cancer Institute in Amsterdam and conducted in part at the UNED in Madrid.
After completing his PhD, van Gerven worked as a postdoctoral researcher at the Institute for Computing and Information Sciences and the Donders Centre for Cognitive Neuroimaging. He created novel brain-computer interfacing paradigms and developed machine learning algorithms for neural data analysis. Subsequently, he was appointed assistant and associate professor at the AI department of the Faculty of Social Sciences. Van Gerven is currently professor of artificial cognitive systems and principal investigator in the Donders Centre for Cognition. He is also chair of the AI department at Radboud University.
My Google citations profile can be found here. My researcher ID can be found here.
Publications
Positions
| 2017 | Full Professor / Principal Investigator Donders Institute for Brain, Cognition and Behaviour Faculty of Social Sciences Radboud University (1.0 fte, fixed-term) |
| 2016 | Associate Professor / Principal Investigator Donders Institute for Brain, Cognition and Behaviour Faculty of Social Sciences Radboud University (1.0 fte, fixed-term) |
| 2010 | Assistant Professor Donders Institute for Brain, Cognition and Behaviour Faculty of Social Sciences Radboud University (1.0 fte, fixed-term) |
| 2009 | Postdoctoral researcher Machine Learning Group, Intelligent Systems Department Institute for Computing and Information Sciences Radboud University (1.0 fte, fixed-term) |
| 2007 | Postdoctoral researcher Machine Learning Group, Intelligent Systems Department Institute for Computing and Information Sciences Radboud University (1.0 fte, fixed-term) |
| 2006 | Visiting researcher Departamento de Inteligencia Artificial UNED, Madrid, Spain |
| 2003 | PhD student Information Retrieval and Information Systems Radboud University Nijmegen (1.0 fte, fixed-term) |
| 2002 | Software Engineer LCN Planning and Scheduling (1.0 fte, fixed-term) |
| 2001 | Visiting Researcher Institute of Ophthalmology University College London, London, UK |
| 2000 | Scientific Programmer Max Planck Institute for Psycholinguistics (1.0 fte, fixed-term) |
| 2000 | Research assistant psycholinguistics Max Planck Institute for Psycholinguistics |
Teaching
Neural Networks
Neural Information Processing Systems
Management
| 2017-present | Head of the AI department |
| 2017-present | Chair of the AI educational programme |
| 2016 | Coordinator of the RU Honours Programme on Wider Implications of Cognitive Neuroscience |
| 2014-2017 | Coordinator of AI Master track ‘Computation in Neural and Artificial Systems’ |
| 2013-2017 | Chair of Bachelor education committee |
| 2013-2015 | Coordinator of the DCC computing cluster |
| 2011-2013 | Internationalization committee member |
| 2010-2013 | Bachelor education committee member |
Education
| 2015 | Academic Leadership |
| 2014 | Masterclass on Theatre in Science |
| 2013 | Extended Academic Teaching Qualification (UKO) |
| 2011 | Academic Teaching Qualification (BKO) |
| 2007 | PhD degree (FNWI) Institute for Computing and Information Sciences Radboud University Nijmegen Thesis: Bayesian Networks for Clinical Decision Support |
| 2000 | Master’s degree in Knowledge Engineering Radboud University Nijmegen Thesis: A model of neural organization: Hierarchical development of the cerebral cortex |
| 1999 | Bachelor’s degree in Cognitive Science Radboud University Nijmegen |
Supervision
Promotions
| 2017 | Max Hinne. Bayesian Connectomics: A Probabilistic Perspective on Brain Networks (cum laude; copromotor) |
| 2017 | Marieke van de Nieuwenhuijzen. Decoding the Perception and Memory Trace: Neuronal Representations of Perceptual and Memory content in Time and Space (copromotor) |
| 2016 | Haiteng Jiang. Characterizing brain oscillations in cognition and disease (copromotor) |
| 2014 | Irina Simanova. In Search of Conceptual Representations in the Brain: Towards Mind-Reading (copromotor) |
| 2012 | Ali Bahramisharif. Covert Visual Spatial Attention: a Robust Paradigm for Brain-Computer Interfacing (copromotor) |
Defense Committees
| 2016 | Simon Jan Hazenberg. Perceptual constructions : Contextual effects on colors, shapes and scenes (examiner) |
| 2016 | Sander Bosch. Reactivating memories in hippocampus and neocortex (examiner) |
| 2015 | Roemer van der Meij. On the identification, characterization and investigation of phase dependent coupling in neuronal networks (examiner) |
| 2015 | Fabian Pedregosa. Feature extraction and supervised learning on fMRI: from practice to theory (examiner) |
| 2014 | Elaine Astrand. Real‐Time Readout of Neural Contents in Visual Perception and Selection in the Non‐human Primate (reviewer, examiner) |
| 2014 | Alex Brandmeyer. Auditory Perceptual Learning via Decoded-EEG Neurofeedback: Towards a Novel Paradigm (reviewer) |
| 2012 | Diego Vidaurre. Regularization for Sparsity in Statistical Analysis and Machine Learning (reviewer) |
| 2011 | Botond Cseke. Variational Algorithms for Bayesian Inference in Latent Gaussian Models (examiner) |
| 2010 | Aritz Perez. Advances in Error Estimation and Multi-Dimensional Supervised Classification (reviewer) |
Grants
| 2017 | TTW Perspective grant Efficient deep learning (co-applicant) |
| 2017 | DCC PhD scholarship: Affective computing in natural and artificial agents (€217K) |
| 2017 | LII BQ1 postdoc position |
| 2017 | STW Perspective grant Neuronal stimulation for recovery of function (co-applicant) |
| 2016 | FAS research assistantship |
| 2016 | DCC PhD scholarship: Visual processing beyond retinal stimulation (€217K) |
| 2016 | NVidia grant |
| 2016 | LII utilisation grant: Aiding people with visual impairments or neurodegenerative disorders by real-time linguistic description of their surroundings |
| 2015 | NWO GO Vidi grant: Peering into the human mind: Decoding internal representations from brain activity (€800K) |
| 2015 | FAS research assistantship |
| 2015 | DCC research assistantship |
| 2015 | DCC feasibility grant (€20K) |
| 2013 | Open Competition NWO EW: Bayesian modeling of brain networks (€217K) |
| 2013 | DCC Postdoc position (€170K) |
| 2012 | DCC PhD scholarship: Connectivity-based prediction of cognitive and motor function (€217K) |
| 2011 | Open Competition NWO MAGW: Decoding the memory trace (€217K) |
| 2010 | Open Competition NWO EW: Sparse learning of deep models (€217K) |
Symposium organisation
| Co-organizer of NVP Symposium on Computational Cognitive Neuroscience 2015 |
| Co-organizer of ICCM workshop on Computational Cognitive Neuroscience 2015 |
| Co-organizer of Donders summer schools (2010, 2013, 2014, 2015) |
| Co-organizer of Pattern Recognition in Neuroimaging workshop 2014 |
| Co-organizer symposium `connectivity and multivariate classification approaches’ at BioMag2010 |
Invited talks (past 5 years)
| 2018 | TUE, Eindhoven. Title: Deep Learning in Cognitive Science |
| 2018 | KTU, Kyoto. Title: Neural Networks as a Window on Human Cognition |
| 2018 | CiNet, Osaka. Title: Neural Networks as a Window on Human Cognition |
| 2017 | IntArt17, Montreal. Title: Artificial Cognitive Systems |
| 2017 | Cosyne, Salt Lake City. Title: ANN-based prediction of neural and behavioral responses in humans |
| 2017 | Karolinska Institutet, Stockholm. Title: Modeling human brain function with artificial neural networks |
| 2016 | UvA, Amsterdam. Title: What artificial neural networks tell us about human brain function |
| 2016 | Bernstein conference workshop, Berlin. Title: Recurrent neural networks as models of cognitive processing |
| 2016 | Charite, Berlin. Title: Modeling Human Brain Function with Artificial Neural Networks |
| 2016 | OHBA, Oxford. Title: Modeling Human Brain Function with Artificial Neural Networks |
| 2016 | IMPRS NeuroCom Summer School, Leipzig. Title: Modeling Human Brain Function with Artificial Neural Networks |
| 2016 | Human Brain Mapping, Geneva. Title: Population Receptive Field Modeling |
| 2016 | ABC Summerschool, Amsterdam. Title: Computational Cognitive Neuroscience |
| 2016 | Netherlands Institute for Neuroscience, Amsterdam. Title: Probing Cortical Representations with Deep Neural Networks |
| 2015 | University of Düsseldorf, Düsseldorf, Germany. Title: Probing Cortical Representations with Deep Learning |
| 2015 | University of Amsterdam. Title: Probing Cortical Representations with Deep Learning |
| 2014 | Osnabrück University, Osnabrück, Germany. Title: Probing Cortical Representations with Deep Learning |
| 2014 | Linköping University, Linköping, Sweden. Title: Probing Cortical Representations with Deep Learning |
| 2014 | Symposium Real-world vision in the brain, UvA, Amsterdam. Title: Learning Representations that Drive Cortical Responses |
| 2014 | Machine learning summer school, DTU, Lyngby, Denmark. Title: Machine Learning for Neural Data Analysis |
| 2014 | HBM educational session on Pattern Recognition for Neuroimaging, Hamburg, Germany. Title: Decoding of Conceptual Representations |
| 2014 | PRNI tutorial, Tübingen, Germany. Title: Something Bayesian |
| 2014 | VSS Conference symposium, St. Petersburg, Florida, US. Title: Learning and Comparison of Visual Feature Representations |
Scholarships and Awards
| 2017 | Best poster award, Donders theme meeting |
| 2016 | Best poster award, Donders theme meeting |
| 2013 | Nominee for the Hermesdorf International award |
| 2013 | Best poster award, Donders theme meeting |
| 2009 | Best poster award, BrainGain Conference |
| 2009 | Winner of the Pittsburgh Brain Connectivity Competition |
| 2007 | Johan Brouwer Fonds, research scholarship (€5K) |
Presentations at international workshops and conferences
International Conference on Cognitive Modeling (ICCM)
Vision Science Society (VSS)
Pattern Recognition in Neuroimaging (PRNI)
International Conference on Artificial Neural Networks (ICANN)
Human Brain Mapping (HBM)
Neural Information Processing Systems (NIPS)
Specialist Group on Artificial Intelligence (SGAI)
Probabilistic Graphical Models (PGM)
Intelligent Data Analysis in Medicine and Pharmacology (IDAMAP)
European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty (ECSQARU).
Reviewing
PLoS Biology, PNAS, Neuroimage, Human Brain Mapping, Machine Learning, Neural Information Processing Systems, CoSyne, Transactions on Biomedical Engineering, International Conference on Machine Learning, Artificial Intelligence in Medicine, Journal of Neural Engineering, International Statistical Review, IEEE Transactions on Medical Imaging, Journal of Neurophysiology.
Committees
Special issue editor for Neuroimage
Special issue editor for Frontiers in Computational Neuroscience
Review editor for Frontiers in Brain Imaging Methods
Review editor for Frontiers in Computational Neuroscience
Program committee member for ICANN 2014
Program committee member for BENELEARN 2013
Program committee member for the IJCNN 2013 special session on Unsupervised Model-Based Learning: Bayesian regularization and Sparsity
Program committee member for Pattern Recognition in Neuroimaging 2012, 2013
External reviewer for De Hersenstichting and Fondazione Bruno Kessler
Societal Impact
Media appearances
| 2018 NRC, Volkskrant |
| 2017 Radio 1: Nieuws en Co, IEEE Pulse |
| 2016 Volkskrant, NRC, Tros Nieuwsshow |
| 2013 Volkskrant, NRC, VPRO Tegenlicht, Radio 1: Met het oog op morgen, BBC World Radio, Wired |
Company involvement
| 2016 Co-founder of CCNLab holding |
Research bodies
| 2015 External advisor for the Human Brain Project |
Public understanding of science
| Company presentations (Almende, ASML) |
| High-schools (beta summer-camp, code-yard project, 4VWO dag, Nijmeegse tweedaagse) |
| Dissemination to the general public (lustrum F.C. Donders Centre for Cognitive Neuroimaging, Lux Researcher’s Night, Alumni dag) |
| Editor of the Donders Institute Newsletter 2014-2017 |
Memberships
| Dutch Neurofederation |
Theses
MAJ van Gerven. Bayesian Networks for Clinical Decision Support. Nijmegen, The Netherlands: Radboud University Nijmegen; 2007.
MAJ van Gerven. A Model of Neural Organization: Hierarchical Development of the Cerebral Cortex. Raboud University Nijmegen; 2000.