Friedemann Zenke, PhD
Principal Investigator
Mattias Nilsson, PhD — Post-doc (since 2023)
Ph.D. in Neuromorphic Computing and M.Sc. in Engineering Physics from Luleå University of Technology, Sweden. I am interested in spiking neural networks and their application on emerging neuromorphic hardware for efficient computation, such as for edge AI applications.
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 (since 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.
Julius Wurzler — Undergraduate (since 2024)
BSc in Bioinformatics, University of Tübingen and BSc in Electrical Engineering, DHBW Friedrichshafen. I am interested in the computational mechanisms that underly biological neural networks and give rise to intelligence.
Collaborators and co-advised students
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, Post-doc
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.
Alumni
- Aaron Spieler (2024) → MSc in Neural Information Processing, University of Tübingen
- Tengjun Liu (2023–2024) → PhD student at Zhejiang University
- Axel Laborieux (2021–2024) → Research scientist, Huawei Research
- Jeremias Seitz (2022–2024)
- Manvi Agarwal (2021–2022) → PhD student, Télécom Paris, Institut Polytechnique de Paris
- Siegfried Schwartz (2022) → CS student (bachelor) at TU Vienna
- Peter Buttaroni (2022) → PhD student, Zenke Lab
- Yue “Kris” Wu (2019–2022) → PhD student, TU Munich
- Nikolaos Papanikolaou (2021–2022) → PhD student, University of Stuttgart, Germany
- Guillermo Martin Sanchez (2021–2022) → PhD student, Champalimaud
- Julia Gygax (2021) → PhD student, Zenke Lab
- Matthias Depoortere (2020) → AI/ML Engineer at GSK Vaccines
- Tianlin Liu (2019–2020) → PhD student, University of Basel
Former collaborators and external students
- Bastian Eichenberger, FMI, PhD student (2020–2023), co-advised with Jeff Chao and Guillaume Diss → Independent consultant
- Sebastian Billaudelle, University of Heidelberg, PhD student (2021–2022), co-advised with Johannes Schemmel → Postdoc, INI, Uni and ETH Zurich
- Benjamin Cramer, University of Heidelberg, PhD student (2019–2022), co-advised with Johannes Schemmel → Staff scientist, Bosch Research