Andreas Stöckel

PhD Student

My research interests are mostly focused on extending the Neural Engineering to work with more detailed neuron models, and using adaptive filtering as a model of sensory inference in the brain.

Regarding my work on more detailed neuron models, I have been working on incorporating simple multi-compartment models with conductance-based synapses into the NEF. The more complex interaction between excitation and inhibition can be systematically exploited to compute functions such as multiplication. Most of this work has been implemented in NengoBio, an extension library for Nengo facilitating the construction of biologically constrained models. I have adapted some of this work to construct a model of eyeblink conditioning the cerebellum.

Regarding my work on adaptive filtering, I am focusing on predictive neural networks based on adaptive state observers.

Apart from these focus areas, I am interested in a broad range of topics including–but not limited to –neuromorphic hardware, neurorobotics, and unsupervised learning strategies.

I defended my PhD thesis in December 2021; please find my thesis here.

I have been teaching SYDE 556/750 "Simulating Neurobiological Systems" in Winter 2020. See here for the lecture notes and slides I prepared for the course.

Prior to joining the CNRG in January 2017, I have been a research assistant at the Cognitronics and Sensor Systems Group in Bielefeld, Germany, where I worked on neuromorphic hardware benchmarks and associative memory as part of the HBP neuromorphics subproject.

In my free time, I am either reading, building free software, tinkering with electronics, writing terrible German fantasy novels, or wandering around aimlessly, getting lost.



Journal Articles

Conference and Workshop Papers

Technical Reports and Preprints