Shih-Chii Liu is professor at the Faculty of Science of the University of Zurich. She co-directs the Sensors Group at the Institute of Neuroinformatics, University of Zurich. Her group works on low-power neuromorphic event-driven sensor design; bio-inspired and deep learning algorithms and hardware for energy-efficient, real-time, adaptive intelligent systems.
In this project, her group will be developing hardware-aware algorithms and real-time hardware accelerators for the vision networks that drive the neural amplifiers.
Tobi Delbruck is adjunct professor at D-ITET and D-PHYS, ETH Zurich. He co-directs the Sensors group at the Institute of Neuroinformatics. He focuses on neuromorphic event sensors and processing, with recent focus on theory and hardware accelerators for AI.
In this project, his group will help in the development of hardware accelerated visual scene parsing.
Hasan Mohamed is a PhD student at the institute of Neuroinfomatics (INI), University of Zurich and ETH Zurich. He obtained his Masters degree in Information Technology from the University of Stuttgart. His masters work focused on accelerating CNN inference using a multi-core CNN accelerator.
In this project, he will be working on the development of a real-time neuromorphic hardware accelerator.
Zuowen Wang is a PhD student at the Institute of Neuroinformatics (INI), University of Zurich and ETH Zurich. He acquired his B.Sc. and M.Sc. degrees in computer science from ETH Zurich. His research interests lie in event-based vision processing, robust deep learning, as well as acceleration and compression of deep learning models.
In this project, he will be working on the development and acceleration of visual scene parsing algorithms.
Pieter R. Roelfsema is director of the Netherlands Institute for Neuroscience and professor at the Free University of Amsterdam and also at the AMC in Amsterdam. He studies visual perception, plasticity and memory in the visual system of experimental animals, humans, and with neural networks. He coordinates the Dutch neurotechnology initiative "NeuroTech-NL"
In this project, his team will contribute neuroscientific knowledge and demonstrate the functionality of the new devices in experimental animals.
Xing Chen is a senior researcher at the Netherlands Institute for Neuroscience, work package co-leader in NeuraViPeR, and manager of the NWO-funded NESTOR programme. Her work in monkeys demonstrated that electrical stimulation of the visual cortex generates recognisable artificial percepts, such as letters and motion. She obtained her PhD in Visual Neuroscience at Newcastle University (UK) and her Bachelor’s in Neuroscience from the University of Southern California.
She specializes in brain-computer interfaces; visual neuroscience; blindness; and chronic recording from and microstimulation of the brain in non-human primates.
Bingshuo Li is a postdoc in the Roelfsema group at the Netherlands Institute for Neuroscience. He obtained his master and doctoral degree in neural and behavioral sciences from the International Max Planck Research School for Cognitive & Systems Neuroscience at the Eberhard Karls University of Tübingen, Germany. His main research interest is on the neuronal mechanisms of brain stimulation. In this project, he will validate the newly developed hardware and algorithms in the rodent visual system.
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.
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.
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 - MSc
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.
Maria Asplund is a group leader at the Albert-Ludwigs Universität Freiburg and Centre of Excellence BrainLinks-BrainTools and the Department of Microsystems Engineering (IMTEK), Microsystems Materials Laboratory. Her research is focused on the development and validation of bioelectronic microtechnology, in particular electrode materials, polymer based flexible microtechnology and biocompatibility.
In NeuraViPeR, her team will develop the high-density stimulation and recording flexible electrode arrays for neural probe implantation into brain tissue
Patrick Ruther is a senior group leader and head of the Neural Implant Group at the Department of Microsystems Engineering (IMTEK), Microsystems Materials Laboratory. His research is focused on the development and validation of CMOS-compatible implants for electro- and optophysiology based on stiff and flexible substrate materials.
In NeuraViPeR, his team will address the high-yield interfacing between flexible neural implants and CMOS ASICs developed by project partner imec as well as tools for neural probe implantation into brain tissue.
Christian Böhler - Postdoctoral Researcher
Christian Böhler is a postdoc at the University of Freiburg, Germany. He obtained his master and doctoral degree in Microsystems Engineering in Freiburg, and continued as a postdoc in the Asplund group. His main research focus is electrode materials and microfabrication of flexible neuroelectronic implants.
In NeuraViPeR, he will be part of developing the electrode technology, in particular refining processes for fabrication and validating long term stability of the electrode materials and implants.
Eduardo Fernández is a qualified MD who combines biomedicine with the physical sciences and engineering to better understand and safely interact with the nervous system. He is also trying to improve our knowledge of brain plasticity in blind subjects and working on the development of new therapeutic approaches for retinal degenerative diseases.
His team will be responsible of the planned experiments in human blind volunteers and the development of new strategies to provide functionally meaningful stimulation to cortical implants.
Leili Soo - Postdoctoral Researcher
Leili Soo is a postdoc at the University Miguel Hernández. She obtained her doctoral degree in Psychology (Science) at the University of Aberdeen (Scotland), focussing on understanding the behavioural and neural mechanisms of visual processing (specializing on visual crowding and attention).
In NeuraViPeR, she is responsible for the testing of human blind volunteers pre- and post-intervention in order to assess the benefit of cortical prosthetic device and advise its future development.
Carolina Mora Lopez - PhD, Principal Investigator
Carolina is a principle scientist and leader of the Circuits for Neural Interfaces team at imec. She received her Ph.D. degree in Electrical Engineering in 2012 from the KU Leuven, Belgium, in collaboration with imec, Belgium. Her team is responsible for innovating, conceiving and delivering all the ASIC and system solutions of our neurotech program.
In this project, her team will design, simulate and test the recording and stimulation ASIC that will interface with the implantable flexible electrodes, as well as the whole acquisition system that controls this chip.
Bogdan Raducanu - PhD
Bogdan Raducanu received the Ph.D. degree from KU Leuven, Belgium, in 2018 in collaboration with IMEC, Belgium, working towards development of high throughput neural implants. He is currently working with IMEC as a Senior Researcher, focusing on designing microelectronic solutions for high density neural interfaces, implantable, and wearable electronics.
In this project, Bogdan will be leading the design of the neural stimulation and recording ASIC that connects to the implantable flexible electrodes. He will also support the development of the data-acquisition system.
Patrick Hendrickx is a design engineer with 30 years of experience in the development and production of electronic systems (HW & SW) for industrial, medical, avionics and space applications. Some of his realizations are module construction for the space projects SWOT & EXOMARS, design of professional GNSS receivers, and development of kernel code for multi-DSP vision inspection systems. Within this project, he is involved in the design and testing of the data-acquisition system for the neural stimulation and readout ASICs developed by imec.
Bert Monna - PhD, Principal Investigator
Bert Monna is CEO of Phosphoenix, a start-up company that will bring visual cortical prosthesis technology to clinical approval.
Please send an email to shih[at]ini.uzh.ch if interested in a doctoral position in machine learning.