Dr Bogdan Grechuk is the programme’s Principal Investigator. He is a member of the School of Mathematics and Actuarial Science at the University of Leicester, specialising in risk analysis and machine learning. He has led risk analysis research in several projects, including the recently funded Innovate UK KTP grant with TG0 Ltd. In 2010, Dr Grechuk et al. developed a theory of generalized Chebyshev inequalities which can be used for robust estimation of the probabilities of rare events. In 2014, he developed with Zabarankin a novel theory for studying the risk of catastrophic events. More recently, he participated in developing mathematical foundations for an error correction mechanism in data-driven artificial intelligence (AI) systems. Dr Grechuk has led undergraduate and MSc modules on the principles of actuarial modelling, with applications to mortality and morbidity modelling.
Prof Alexander Gorban is the Director of the Centre for Artificial Intelligence, Data Analysis and Modelling (AIDAM) and Professor of Applied Mathematics at the University of Leicester. He is known for the development of algorithms for the fast learning of neural networks, methods for dimensionality reduction in machine learning and beyond, applied data mining projects, and recently developed the technology of AI correctors. He is the Academic Leader in three Innovate UK KTP grants and a Co-Investigator of a £1M AHRC grant on using AI and Machine Learning in Archaeology. He was a visiting professor and research scholar at the Clay Mathematics Institute, IHES, Courant Institute, and Isaac Newton Institute. He has active academic collaborations with IHES, ETH Zurich, Institut Curie, Saint Louis University, Eindhoven University of Technology, and Toyota Technical Centre, Ann Arbor. He has been the Principal Investigator of various EPSRC, Royal Society, LMS and British Council projects for the organisation of research workshops and the development of international scientific collaboration. Among his collaborators and co-authors are two Presidents of the International Neural Network Society, D. Wunsch and D. Prokhorov. Prof Gorban was an invited plenary speaker at the 2020 IEEE World Congress of Artificial Intelligence. He has over 11,000 citations with an h-index of 51 on Google Scholar.
Dr Evgeny Mirkes has experience in practical data analysis and the implementation of various data-driven models, including models for mortality evaluation, risk evaluation. His main research interests are biomathematics, data mining and software engineering, neural network and artificial intelligence. He has led and supervised many projects in data analysis and the development of decision-support systems for computational diagnosis and treatment planning, and has participated in applied projects in Natural Language Processing in the area of social media data analysis. He has rich experience in Predictive Mathematical and Computational Modelling and in finding solutions to classification, clustering and auto coding problems. In particular, he developed a special programming language for Neural Networks, created a theory on geometrical complexity which is applicable to approximators of several types and allows the comparing of various methods of data approximations. He elaborated a new and universal framework to minimise arbitrary sub-quadratic error potentials in machine learning and developed new machine learning methods, which achieve orders of magnitude with faster computational performance than corresponding state-of-the-art methods.
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