Felix Schürmann

Felix Schürmann
École Polytechnique Fédérale de Lausanne
Lausanne, Switzerland

Keynote lecture

Will talk about: In silico neuroscience – an integrative approach

Bio sketch:

Felix Schürmann is adjunct professor at the Ecole Polytechnique Fédérale de Lausanne, co-director of the Blue Brain Project and involved in several research challenges of the European Human Brain Project. He studied physics at the University of Heidelberg, Germany, supported by the German National Academic Foundation. Later, as a Fulbright Scholar, he obtained his Master's degree (M.S.) in Physics from the State University of New York, Buffalo, USA, under the supervision of Richard Gonsalves. During these studies, he became curious about the role of different computing substrates and dedicated his master thesis to the simulation of quantum computing. He studied for his Ph.D. at the University of Heidelberg, Germany, under the supervision of Karlheinz Meier. For his thesis he co-designed an efficient implementation of a neural network in hardware.

Talk abstract:

Many areas of science and engineering have adopted simulation-based research as a novel tool for discovery and insight. The sustained performance growth in supercomputer performance allows ever more detailed models, which makes supercomputing nowadays also a viable tool for biology. However, the heterogeneity of neural systems poses particular challenges: the data is multi-modal, multi-scale and often times incomplete; intricate workflows are required for model generation and mathematical formulations are volatile; due to the heterogeneity requirements of memory and compute are demanding. At the same time, neurobiology has potentially a lot to gain: systematically accounting for the data and bringing it together in a unifying computer model provides an integration strategy capable of overcoming the fragmentation of data and identifying gaps in our knowledge. Attempting this ultimate integration is revealing novel design principles of the brain. These principles are in turn helping to predictively fill gaps in data and knowledge. As a proof of concept, the Blue Brain Project built a facility comprised of many key technologies and workflows and used this facility to build and simulate a unifying model of the neocortical microcircuit of the young rat.