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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 ( He is the Director and the Founder of the Knowledge Engineering and Discovery Research Institute (KEDRI, 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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Aug 27, 2014 Scott, N., N. Kasabov and G. Indiveri, NeuCube Neuromorphic Framework for Spatio-Temporal Brain Data and Its Python Implementation, Proc. ICONIP 2013, Springer LNCS, vol.8228, pp.78-84.
Aug 27, 2014 Kasabov, N., E.Capecci, Spiking neural network methodology for modelling, classification and understanding of EEG spatio-temporal data measuring cognitive processes, Information Sciences, DOI: 10.1016/j.ins.2014.06.028, 2014.
Aug 27, 2014 Kasabov, N. et al, (2014). Evolving Spiking Neural Networks for Personalised Modelling of Spatio-Temporal Data and Early Prediction of Events: A Case Study on Stroke. Neurocomputing, vol .134, 269-279, 2014
Aug 27, 2014 Kasabov, N. NeuCube: A Spiking Neural Network Architecture for Mapping, Learning and Understanding of Spatio-Temporal Brain Data, Neural Networks vol.52 (2014), pp. 62-76,
Nov 17, 2012 Training Spiking Neural Networks to Associate Spatio-temporal Input-Output Spike Patterns
Nov 17, 2012 Spiking neural network architecture for associative learning of spatio-temporal brain patterns
Nov 17, 2012 Dynamic Evolving Spiking Neural Networks for On-line Spatio- and Spectro-Temporal Pattern Recognition
Nov 17, 2012 Evolving Spiking Neural Networks for Spatio and Spectro-Temporal Pattern Recognition, Plenary talk IEEE IS
Nov 17, 2012 Mapping, Learning and Mining of Spatiotemporal Brain Data with 3D Evolving Spiking Neurogenetic Models
Nov 17, 2012 Evolving spiking neural networks: A Survey

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