D. Nowicki was graduated from Moscow Institute of Physics and Technology (MIPT) in applied mathematics and physics in 2000. He has a Ph. D. in Computer Science from Institute of Cybernetics of NASU and a Ph. D. in applied mathematics from Universite Paul Sabatier, Toulouse, France Dimitri’s work experience includes research in universities of Toulouse and Grenoble, France as well as University of Massachusetts and Harvard, USA. He is one of the leaders of the volunteers’ neurosicience Rybka Project.
Topic: Spiking models and neuromorphic computing
Short Description: Now we live in the Deep Learning Era, and its triumph made us to forget that “deep” neural networks as well as “shallow” ones consist of the same McCulloch-Pitts Neurons, which were invented in 1943. Such neurons are quite different from human (or e.g. rat) ones.Every real brain’s neuron is in fact a special-purpose processor. In this presentation we will talk about biologically plausible neurons and their networks; modeling and training of spiking networks. We will review open problems in this domain. Next, we will present neuromorphic hardware including memristor based neurons. These technologies lead to hardware implementation of brain-like neuromorphic computing.