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Nikola Kasabov

Prof. Nikola K. Kasabov is Marie Curie Fellow and Visiting Professor at the Institute for Neuroinformatics, ETH/UZH funded by the EU Marie Curie IIF EvoSpike Project (http://ncs.ethz.ch/projects/evospike). He is the Director and the Founder of the Knowledge Engineering and Discovery Research Institute (KEDRI, www.kedri.info) and Professor of Knowledge Engineering at the School of Computing and Mathematical Sciences at the Auckland University of Technology, New Zealand. He is Fellow of IEEE and Distinguished IEEE CIS Lecturer (2011-2013), also a Fellow of RSNZ. He obtained his Masters degree in computing and electrical engineering (1971) and PhD in mathematical sciences (1975) from the Technical University of Sofia, Bulgaria where he worked until 1998. Afterwards he has also worked at the University of Essex, UK and the University of Otago, NZ. He has published more than 450 papers, books and patents in the areas of computational intelligence, neural networks, bioinformatics, neuroinformatics. Prof. Kasabov was the President of the International Neural Network Society (INNS) for 2009 and 2010 and now he is a Governor of INNS. He is a Past President of the Asia Pacific Neural Network Assembly (APNNA) and a Guest Professor at the Shanghai Jiao Tong University. Among his awards are the INNS Gabor Award (2012), the Bayer Innovation Award (2007), the APPNA Excellence Award (2005), the RSNZ Science and Technology Medal (2002) and numerous IEEE best paper awards. He has given more than 50 keynote and plenary talks at international conferences and served as a chair and a committee member of numerous IEEE, ICONIP, ANNES and other international conferences. More than 35 PhD students have graduated under his supervision.
Location: INI/ETH/UZh Zurich and KEDRI/AUT, Auckland NZ

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Dec 05, 2017 A Spiking Neural Network Methodology and System for Learning and Comparative Analysis of EEG Data from Healthy versus Addiction Treated versus Addiction Not Treated Subjects
Dec 05, 2017 Training spiking neural networks to associate spatio-temporal input–output spike patterns
Dec 05, 2017 An improved collaborative representation based classification with regularized least square (CRC–RLS) method for robust face recognition
Dec 05, 2017 FROM MULTILAYER PERCEPTRONS AND NEURO-FUZZY SYSTEMS TO DEEP LEARNING MACHINES: WHICH METHOD TO USE? - A SURVEY
Dec 05, 2017 Spiking neural network methodology for modelling, classification and understanding of EEG spatio-temporal data measuring cognitive processes
Dec 05, 2017 Longitudinal Study of Alzheimer's Disease Degeneration through EEG Data Analysis with a NeuCube Spiking Neural Network Model
Dec 05, 2017 Analysis of connectivity in a NeuCube spiking neural network trained on EEG data for the understanding and prediction of functional changes in the brain: A case study on opiate dependence treatment
Dec 05, 2017 Adaptive Cow Movement Detection using Evolving Spiking Neural Network Models
Nov 28, 2017 Spiking Neural Networks for Crop Yield Estimation Based on Spatiotemporal Analysis of Image Time Series
Nov 28, 2017 NeuCube for obstacle avoidance in simulated prosthetic vision

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