Alexander N Gorban

Alexander N Gorban

Alexander N Gorban

Monday, 20th July, 2020

Professor of Applied Mathematics and Director of the Centre for Mathematical Modelling at the University of Leicester (UK), Alexander worked for Russian Academy of Sciences, Siberian Branch, and ETH Zürich, was a visiting professor and research scholar at Clay Mathematics Institute (Cambridge, MA), IHES (Bures-sur-Yvette, France), Courant Institute of Mathematical Sciences (New York), and Isaac Newton Institute for Mathematical Sciences (Cambridge, UK). His main research interests are machine learning, data mining and model reduction problems, and dynamics of systems of physical, chemical and biological kinetics.

At the XIX International Conference “Neuroinformatics-2017” (Moscow, 2017), the Russian Neural Network Society awarded Alexander the honorary title “Pioneer of Russian Neuroinformatics” (No. 1) for his “Extraordinary contribution to the theory and applications of artificial neural networks.” His first book about neural networks with elements of deep learning was published in 1990 (“Training Neural Networks”, USSR-USA JV “ParaGraph”). This book was focused on the problem of fast and reliable learning of neural networks. In the 1990s, Alexander invented and implemented methods to transform neural network skills into an explainable (“logically transparent”) form, and applied them to many real-life problems, from health care to psychological and political consultations. He developed several generations of approaches to dimensionality reduction in data analysis and kinetic modelling. For the applications of these methods in chemical and physical kinetics and for the contribution to the solution of 6th Hilbert problem Alexander was awarded by Prigogine Medal (2003). Recently, the methods of elastic graphs and topological grammars developed by Alexander and his collaborators have demonstrated their effectiveness in bioinformatics for analysing single cell omics data. During last decade, Alexander and his team have developed a new technology to correct errors of artificial intelligence systems in the processing of multidimensional data. These methods have been successfully used for correction of image recognition in security systems and other applications.

Alexander published more than 200 papers, 19 books, has several patents and organised many conferences and workshops in Neural Networks, Data Analysis, Mathematical Modelling and related topics.

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