Dr Roman Belavkin

Roman Belavkin obtained MSc in Physics from the Moscow State University and PhD in Computer Science from the University of Nottingham.  His research interests span several areas including geometric analysis of optimal and learning systems, dynamics of information, value of information, quantum information, topology of information, geometry and combinatorics of mutation and recombination of sequences, optimal control of evolutionary algorithms, cognitive modelling.  Roman joined Middlesex University in 2002, where he participated in several research projects and organized research seminars of the Artificial Intelligence group.  From 2009 Roman has been the Principle Investigator of the EPSRC project `SANDPIT: Evolution as an Information Dynamic System', which was led by Middlesex University in collaboration with Universities of Manchester, Keele and Warwick.  In this project, Roman developed a theory of optimal control of mutation rate in evolutionary systems, and the team discovered plastic mutation rates in microbes (https://doi.org/skb , https://doi.org/cb9s).  Roman's current work is on geometric and dynamic value of information theory, which has applications in parameter control and optimization of learning, adaptive and evolving systems.  Roman has many international collaborations: He has been an associate member of the `Centre of Applied Optimization' in the University of Florida, USA; his collaboration with Tokyo University of Science was recognized in 2014 by the award from the university's president Professor Akira Fujishima.  Roman has been a keynote speaker at many international conferences, workshops and research seminars.  He also serves on the editorial board of the `Optimization Letters' and `SN Operations Research Forum' journals.