My main research goal is to better understand the underlying mechanisms of the visual system by developing models that strike an effective balance between biological realism and cognitive function. My interest in visual perception, the visual hierarchy, and predictive coding theories was sparked during my Bachelor’s in Cognitive and Neurobiological Psychology. The opportunity of modeling these processes in the brain excited me even more during my Master’s in AI, where I was introduced to brain-inspired models and computer vision.
As a PhD candidate in Cognitive Neuroscience at Maastricht University, I now explore these possibilities by developing a personalized, brain-derived generative model of mental imagery. My current focus is on creating a novel, biophysics-informed modeling approach that uses laminar-resolved cortical columns as building blocks for continuous-time neural networks. This approach allows embedding functionality while biological realism is maintained through neuroanatomical constraints. I thoroughly enjoy integrating my interests and expertise in this project, as well as working collaboratively in an interdisciplinary team in which we together aim to unravel the mechanism behind mental imagery.