Friedemann Zenke, PhD
Principal Investigator

about and bio

Axel Laborieux, Post-doc (since 2021)
PhD in Neuromorphic Computing at Paris-Saclay University.
I am interested in understanding the link between cortical circuit motifs and their associated functional roles for efficient information processing in spiking neural networks.

Peter Buttaroni, PhD student (since 2022)
MSc in Quantitative Finance at Luiss Guido Carli (IT) and MSc in AI from the Università della Svizzera Italiana (CH). I am interested in Reinforcement Learning algorithms and how biological principles can be used to improve artificial neural networks.

Julia Gygax, PhD student (since 2022)
BSc in Electrical Engineering and Information Technology, ETHZ. MSc in Biomedical Engineering from ETHZ. I am interested in how concepts of biological neural networks can be applied to artificial neural networks and in training of spiking neural networks.

Manu Srinath Halvagal, PhD student (since 2020)
M.Sc, Microengineering with a minor in Computational Neuroscience, EPFL and B.Tech, Electrical Engineering, IIT Madras. I am interested in the mechanisms of unsupervised and self-supervised perceptual learning in networks of biological neurons, and the role of top-down connections therein. I am also interested in exploring whether we could use these principles to improve machine learning algorithms.

Ashena Gorgan Mohammadi, PhD student (starting 2023)
MSc in Computer Science from University of Tehran. My main interest is to develop bio-plausible intelligent systems in broad terms. More specifically, I am interested in how we can simulate predictive and continual learning in a spiking model of columnar architecture of the neocortex.

Julian Rossbroich, PhD student (since 2020)
Joint MSc in Neuroscience from Université Laval and Université de Bordeaux. My main interest concerns the neuronal signatures of learning and memory. Specifically, I am interested in how cortical circuits compute predictions of sensory inputs, and how such predictive processing is involved in learning and plasticity.

Jeremias Seitz, PhD student (since 2022)
MSc in Mechanical Engineering with a focus on Robotics and Control Engineering, ETHZ. My interest lies in optimization and control theory. I apply these ideas to learning strategies in neural networks.

Collaborators and external students

Team Heidelberg: Benjamin Cramer (PhD), Sebastian Billaudelle (PhD), with Johannes Schemmel University of Heidelberg.

Bastian Eichenberger, PhD student
with Guillaume Diss and Jeff Chao, FMI.

Claire Meissner-Bernard, Post-doc
with Rainer Friedrich, FMI.

Simon Narduzzi, PhD student
co-advised by Shih-Chii Liu, Institute of Neuroinformatics (UZH/ETHZ) and L. Andrea Dunbar, CSEM.
MSc in computer science and computational neuroscience (EPFL). My research focuses on developing efficient neural networks for ultra-low power neuromorphic hardware.

Luke Taylor, PhD student
co-advised with Nicol Harper and Andy King, University of Oxford.
MSc Neuroscience (Oxford), BSc Applied Mathematics and Computer Science (UCT). I am interested in training spiking neural networks and exploring their applicability to studying the brain.