Friedemann Zenke, PhD
Manu Srinath Halvagal, PhD student (from Aug 2020)
M.Sc, Microengineering with a minor in Computational Neuroscience, EPFL (CH) and B.Tech, Electrical Engineering, IIT Madras (IN). 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.
Julian Rossbroich, PhD student
Joint MSc in Neuroscience from Université Laval (CA) and Université de Bordeaux (FR). 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.
Yue Wu, PhD student
M.Sc. Electrical Engineering and Information Technology, Technical University of Munich, Germany. I am interested in how learning, neural dynamics, and network structure are affected by the interactions of diverse forms of plasticity operating on different time scales.
Matthias Depoortere, Summer Intern 2020
MSc neuroscience student at the University of Freiburg. I’m interested in applying machine learning techniques to neural circuit data to dissect their internal function and in applying these insights to build data-driven models.
Benjamin Cramer, PhD student
with Karlheinz Meier and Johannes Schemmel
Kirchhoff Institute of Physics
University of Heidelberg
BSc Math and MSc Data Engineering, Jacobs University Bremen, Germany. I am interested in the mechanistic underpinnings of neural computation — how do real biological systems compute and how can we mimic their functionality using computer algorithms. My webpage is tianlinliu.com.