Professor Nikola Kasabov, Director of the KEDRI Research Institute, Auckland University of Technology
The talk presents briefly the main principles used in AI, from Aristotle’s true/false logic, through fuzzy logic, evolutionary computation and neural networks, to arrive at the current state-of-the-art in AI – the deep learning machines. One particular such machine, developed in the presenter’s KEDRI institute and dubbed NeuCube, is designed for deep learning of complex data patterns so as to predict future events. It uses the latest AI technique called spiking neural networks (SNN) that mimics the learning capabilities of the human brain. NeuCube has already demonstrated its usefulness when dealing with big data such as brain EEG and fMRI data; brain-computer interfaces; seismic data; and environmental data for stroke prediction. This is the beginning of understanding complex patterns of changes of variables in space and time, and their relevance to future events. It will have a significant impact on our understanding of the dynamics of the micro and the macro worlds with particular application in medicine.
Nikola Kasabov hails from Bulgaria where he received his PhD (Mathematical Sciences) in 1975 from the Technical University of Sofia. He moved to the University of Essex in the UK and, in 1992, to New Zealand as a senior lecturer in the Department of Information Sciences at the University of Otago, quickly advancing to a professorship by 1999. He moved to AUT in 2002 where he is now the Director of the Knowledge Engineering & Discovery Research Institute and holds a Personal Chair of Knowledge Engineering in the School of Engineering, Computer and Mathematical Sciences. He has published over 600 works, including 180 journal papers, 12 text books and 28 patents. He has received numerous awards for the quality of his research output. He is a Fellow of the IEEE, the IITP and the RSNZ.
Professor Kasabov has research interests in neurocomputation, artificial intelligence (neural networks, fuzzy systems, evolutionary computation), machine learning, data mining and knowledge engineering, neuroinformatics, bioinformatics, signal, speech and image processing. Much of his current research in the KEDRI institute is based around his NeuCube neurocomputing technology which is being applied to deep learning and pattern recognition of spatio-temporal data to predict future events such as strokes and earthquakes. More information, along with software and data, can be found at http://www.kedri.aut.ac.nz
Drinks and nibbles will be served from 6pm on Level 1 of the Owen G Glenn building