I received my PhD from Maastricht University in 2016. My PhD project, which I conducted under supervision of Prof. Dr. Rainer Goebel and Prof. Dr. Gustavo Deco, focused on the integration of neuroimaging with computational neuroscience to study information processing in early visual cortex as well as large-scale cortico-cortical network dynamics. After obtaining my PhD, I joined the Human Brain Project and began work as a postdoctoral researcher at the Department of Cognitive Neuroscience. Since that time, my interests have expanded to include (visual) perceptual learning and visuomotor integration and I got exposed to deep learning and neurorobotics. Continuing the integrative spirit of my PhD project, my work fuses neuroimaging, computational modeling, goal-driven deep learning and neurorobotics. Apart from my scientific work, I supervise PhD and Master students, develop software (I contributed to version 2.16 of the NEST simulator and released a toolbox for population receptive field mapping) and teach Bachelor and Master level courses on computational neuroscience, critical thinking and Perception.
In 2015 I obtained my research MSc in Cognitive Neuroscience at Maastricht University. My PhD was supervised by Prof. Dr. Rainer Goebel and Dr. Mario Senden and is part of the NWO-funded NESTOR project. NESTOR is a 4-year programme with the goal to develop a neuroprosthesis that interfaces with the brain, allowing the generation of artificial visual percepts even when there is extensive damage to the eye or the optic nerve. My contribution to this project is to non-invasively map out the anatomy of the visual cortex in blind people, which is required to carry out the necessary pre-surgical planning for electrode implantation. Next to this work, we strive for a better understanding of the human visual system by combining machine learning techniques with (real-time) high-resolution fMRI to recover seen and imagined visual percepts from the brain.
With a background in Electrical Engineering, I obtained my master's degree in Artificial Intelligence from Maastricht University. My fascination with neural networks led me to explore the world of computational neuroscience. In 2023, I earned my PhD degree under the supervision of Prof. Dr. Rainer Goebel and Dr. Mario Senden. My research focused on efficiently mapping population receptive fields and connective fields using computational methods that enable real-time processing. Currently, I am working as a Postdoctoral researcher at the same lab, where my focus lies in network neuroscience and whole-brain modeling. Additionally, I am passionately drawn to the captivating field of data-driven dynamics and model discovery. I thoroughly enjoy acquiring knowledge about novel data-driven methods that uncover hidden patterns and dynamics within extensive datasets, ultimately providing new insights into the functioning of the brain.
With a background in Cognitive Science (University of Osnabrück) and Artificial Intelligence (Maastricht University), I conduct my PhD research at the intersection of neural network modelling and neuroimaging within the Human Brain Project. My work aims at developing deep learning solutions towards visual saliency prediction and integrating the results in a closed sensorimotor loop from natural visual input to eye movements. Furthermore, I am interested in linking computational models to neural activity by encoding and decoding the representational content in fMRI data.
Coming from an engineering background, my bachelor thesis on bio-inspired computer vision steered me towards trying to understand the brain better. To further this interest, I pursued a Master's degree in Cognitive Neuroscience at Maastricht University. During my master thesis, I worked on developing a macroscopic model of saccade generation under the supervision of Dr. Gorka Zamora-Lopez and Prof. Gustavo Deco at UPF Barcelona. As a PhD candidate, I am involved in developing biophysically-plausible models of the visuomotor system and currently focus on target selection. My broad interest lies in using dynamical systems theory to understand neural mechanisms of cognition.
In my bachelor’s degree I studied neuroscience at Maastricht University. I completed my thesis under Prof. Peter de Weerd on the role of oscillations in perceptual learning. To further enhance my knowledge of visual processing I completed a Research Master in Cognitive and Clinical Neuroscience at Maastricht University. My master thesis was an investigation on the effect of internal models on visual short-term memory under Prof. Lars Muckli at the University of Glasgow. During my master’s degree I developed a strong interest in the development of biologically plausible AI systems, which I hope to research in my role as a PhD candidate.
As intelligent systems attempt to mimic human cognition we should explore their biological counterpart for inspiration: the human brain. Intrigued by this very intuition, I received my master's degree in Artificial Intelligence summa cum laude from Maastricht University. In my master thesis, I integrated the lateral connectivity of primary visual cortex into convolutional neural networks under supervision of Dr. Kurt Driessens and Dr. Mario Senden. As a PhD candidate, I now research biologically inspired deep (reinforcement) learning architectures and algorithms as part of the Human Brain Project. To that end, I am interested in the translation of cognitive architectures into deep neural network models to autonomously find flexible policies using reinforcement learning. Additionally, I am keen to improve the biological plausibility of these architectures by integrating cortical connectivity patterns within or between individual layers.