Keynote Speakers
Yevgeniy Bodyanskiy
Fast learning algorithm for GMDH-SVM deep neural network in Data Stream Mining tasks
Professor of Artificial Intelligence Department and Head of the Control Systems Research Laboratory at Kharkiv National University of Radio Electronics. In 1971 he graduated with honour from Kharkiv National University of Radio Electronics. In 1980 he defended the Ph.D. thesis. In 1984 he received an academic title of Senior Researcher. In 1990 he defended the Doctor Thesis (Dr. habil. sc. ing.). In 1994 he received an academic title of Professor. Since 1974 he has been working at Kharkiv National University of Radio Electronics. He has more than 670 scientific publications, including 40 inventions and 13 monographs. Senior Member of IEEE.
Research interests include hybrid systems of computational intelligence: adaptive, neuro-, wavelet-, neo-fuzzy-, real-time systems, including problems connected with control, identification, forecasting, clustering, diagnostics, fault detection in technical, economical, medical and ecological objects.
Viktor Krylov
Image segmentation in the wavelet domain
Prof. of applied mathematic and IT department (Odessa national polytechnic university). Graduated from Odessa Polytechnic Institute in 1978, PhD (1986), Dc. Sc (2002), Prof. (2005). IEEE Member. He has more than 330 scientific publications.
Research interests include image processing and pattern recognition, wavelet analysis, systems of computational intelligence, including problems connected with control, identification, forecasting, clustering, diagnostics, fault detection in technical, medical and ecological objects.
Leonid Lyubchyk
Real-time Ranking Learning from Data Stream
Head of Computer Mathematics and Mathematical Modeling Department, National Technical University "Kharkiv Polytechnic Institute". Graduated from Kharkiv Polytechnic Institute in 1973, PhD (1979), Dc. Sc (1995), Prof. (2001). Ukrainian State Prize Winner in Science and Technology, 1997. IEEE Member, New York Academy of Sciences Member. Leading Research Scientist and Information & Control Systems Expert of State Scientific and Technical Center of Nuclear and Radiation Safety of Ukraine, 2000-2008. Visiting professor in Safety Control Engineering Group, Wuppertal University, Germany, 2001, Automatic Control Department, Center of Investigation and Advanced Education (CINVESTAV), Mexico, 2011.
Research interests are control theory, robust control, system modeling and simulation, computational intelligence and statistical machine learning.
Volodymyr Mashtalir
Sequential temporal video segmentation via spatial image partitions
Prof. of informatics department (Kharkiv National University of Radio Electronics). M.S. thesis: ‘Parallel image processing under projective transformations’ (1979), Ph.D. thesis: ‘3-D objects recognition on the base of its image normalization’ (1984), D.Sc. thesis: ‘Point-to-set methods of image processing and recognition’ (2002).
Research interest: image processing and recognition, models and methods of granulation on the base of clustering and multialgebraic systems, metrical analysis of quotient sets.
Oleksandr Mikhalyov
Synthesis of criteria for the chaotic system identification
Dr. Sc., Professor. Laureate of State prize of Ukraine in science and technology (2014).Head of information technologies and systems department National metallurgical academy of Ukraine (NMetAU, Dnipropetrovsk). Was awarded with signs "Excellence in Education of Ukraine" (1999) and “For Scientific Achievements” (2012 ) of Ministry education and science of Ukraine
Scientific interests in field of the theory of adaptive identification and neuro-fuzzy control of nonlinear dynamical systems, network technologies; mathematical simulation of technological processes and data mining, the fractal material science and applied synergy.
Eduard Petlenkov
Artificial Intelligence Methods for Data based Modelling and Analysis of Complex Processes: Real Life Examples from Industry to Human.
Associate Professor in the Faculty of Information Technology at Tallinn University of Technology, Head of the Estonian National Doctoral School in Information and Communication Technology, Head of Computer Systems Study Programme, Head of Control Systems Research Laboratory.
He received his B.Sc, M.Sc and PhD degrees in computer and systems engineering from Tallinn University of Technology. His main research interests lie in the domain of nonlinear control, system analysis, computational intelligence, industrial software, virtual and augmented reality.
Volodymyr Stepashko
Self-Organizing Intelligent Modeling from Data Stream
Head of department “Information Technologies of Inductive Modeling” at the International Research and Training Centre for Information Technologies and Systems of NAS and MES of Ukraine, Kyiv. Graduated from Lviv State University, Ukraine, M. Sc in radiophysics (1970), Cand. Sc (PhD) in technical cybernetics (1976), Dr. Sc in system analysis (1994), Professor in AI systems and tools (2011). Fields of interest: inductive modeling, data analysis, computational intelligence, information technologies, machine learning, data/knowledge mining, decision making support, predictive control. Fields of application: technologies of modeling, evaluation, forecasting and decision support for economical, ecological, biological and technical processes and systems.
Kristina Vassiljeva
Artificial Intelligence Methods for Data based Modelling and Analysis of Complex Processes: Real Life Examples from Industry to Human
Associate Professor in the Faculty of Information Technology at Tallinn University of Technology, Alpha Control Laboratory and Re:creation Visual and Augmented Reality Laboratory. She received her B.Sc, M.Sc and PhD degrees in computer and systems engineering from Tallinn University of Technology. Her research interests include systems of computational intelligence, industrial software, virtual and augmented reality.
Margaret Ostapchuk
Teсhnical Evangelist, Microsoft Ukraine Margaret's job is in the department of strategic researches of Microsoft Ukraine. Primary specializations are Windows development and Microsoft Azure development.
Big Data in Cloud
Deliver instant and useful insight to gain a competitive advantage for your organization is becoming increasingly difficult due to the increased variety and velocity of data. The panel will allow you to understand the services that help a developer to store, analyze, predict and visualize large data. We'll consider an example for social networks data processing.