tl;dr? Looking for something shorter? There is a short 3rd person version here.
By training I am a physicist and worked in nuclear and medium energy particle physics in the groups of Professor Hinde in Canberra, Australia and Professors Beck and Thoma at the Crystal Barrel experiment in Bonn, Germany. I obtained my diploma in physics in March 2009. I then moved fields and did my PhD in theoretical neuroscience in the group of Wulfram Gerstner in Lausanne, Switzerland. My thesis was on associative memories and how they can form in recurrent neural networks in an unsupervised manner. As a post-doc I have the privilege to work with Surya Ganguli at Stanford and Tim Vogels at the University of Oxford.
I am interested in biologically plausible learning and memory in (spiking) neural networks. To that end, I study the interplay of homeostatic, inhibitory and excitatory plasticity with the ultimate aim to understand how these components interact to form non-random networks that serve a particular purpose. I use tools from deep learning, dynamical systems and control theory. To verify analytical results, I run large-time-scale simulations which are pushing the boundaries of high-performance computing. My efforts behind this are reflected in the open source simulation software Auryn for spiking neural networks which I develop actively.