Prof. Karlheinz Meier

Prof.Dr. Karlheinz MeierKirchhoff-Institute for Physics

Karlheinz Meier is a professor of experimental physics at Heidelberg University in Germany. He received his PhD in 1984 from Hamburg University. For more than 30 years he worked in experimental particle physics, contributing to several experiments at the CERN and DESY laboratories. He designed and implemented a large-scale data selection system for an LHC experiment at CERN: Since 2005 he has shifted his interest towards custom hardware implementations of neural circuits. He has initiated and led 2 major European initiatives in the field (FACETS and BrainScaleS) and is currently co-director of the Human Brain Project.

The Human Brain Project – From Biological Foundations to new Computing Architectures

The EU has recently approved the Human Brain Project (HBP) as one of 2 European research flagships. The HBP will provide new tools to help understand the brain and its fundamental mechanisms and to apply this knowledge in future medicine and novel computing architectures. Central to HBP is Information and Communication Technology (ICT). The project will develop 6 ICT platforms for neuroinformatics, brainsimulation, medical informatics, supercomputing, neuromorphic computing and neurorobotics that will make it possible to federate neuroscience data from all over the world, to integrate the data in unifying models and simulations of the brain, to check the models against data from biology and to make them available to the world scientific community. Among the final goals of the project is the transfer of brain-derived computing principles to new computing architectures. Physical models of neural circuits have been explored over many decades. They attempt the electronic implementation of brain features like low power operation, fault tolerance and in particular the ability to learn and to make predictions based on the results of the learning process. Nonetheless such systems have so far failed to outstrip conventional von Neumann devices. The lecture will review existing work and point to important developments in neuroscience, engineering and theory that may contribute to make brain derived computing a competitive technology.