Donders Institute, Radboud University
Marcel van Gerven is professor of artificial cognitive systems and chair of the AI department at the Donders Institute for Brain, Cognition and Behaviour, Radboud University. His group develops new brain-inspired neural network models and machine learning techniques for inference and control of complex systems.
In this project, his team will develop efficient neural network models for phosphene vision and algorithms for closed-loop control of neural systems.
Bodo Rueckauer - Postdoctoral Researcher
Bodo Rueckauer is a postdoc at the Donders Institute for Brain, Cognition and Behaviour, Radboud University. He obtained his B.Sc. and M.Sc. degrees in physics from ETH Zurich. His PhD work at the Institute of Neuroinformatics (University of Zurich) focused on event-based vision processing in deep spiking neural networks.
In this project, he is working on control methods for self-calibrating neural stimulation.
Burcu Küçükoğlu - PhD Student
Burcu Küçükoğlu is a PhD student at the AI department of the Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen. She obtained her Masters degree in Artificial Intelligence from Vrije Universiteit Amsterdam. Her general interests lie in augmenting human capabilities with the help of intelligent artificial systems to empower people in reaching their full potential.
In this project, she will be focusing on developing brain-inspired models to optimise phosphene vision using artificial reinforcement learning agents, aiming for efficient closed-loop control of neural implants.
Yağmur Güçlütürk is an assistant professor at AI Department of the Radboud University and Donders Institute for Brain, Cognition and Behaviour. She uses various computational modeling and psychophysics techniques as well as utilizing new technologies such as deep learning and augmented/virtual reality to develop and test neuroprosthetics applications, and to study human perception.
In the NeuraViPeR project, together with Marcel van Gerven, she will oversee the development of efficient neural network models for phosphene vision and algorithms for closed-loop control of neural systems.