Senior Research Fellow
School of Digital Technologies
Mikhail is a statistical physicist with background in complex networks, random processes, soft condensed matter and biophysics. He is interested in applying the ideas and methods developed in statistical physics to various types of human-generated data.
Mikhail is a theoretical physicist, he defended his PhD at Moscow State University, for 2 years he was a postdoc at the University Paris Sud in France, and then for many years worked in Moscow, teaching statistical physics and soft condensed matter at Moscow State University, Higher School of Economics and Moscow Physical-Technical Institute. He co-authored more than 40 papers in peer-reviewed research journals, mostly in the fields of physics of polymers and biopolymers, complex network theory, random walks and random growth processes.
Mikhail is interested in application of methods of statistical physics and complex networks to human-generated data, in particular he has experience working with data of demographic (covid-related), transport (patterns of human movement) and psycholinguistic (free associations networks) nature. He is interested, among other things, in optimal embedding of networks in metric spaces, dimensional reduction, community detection, temporal patterns of human activity, abrupt transitions in social systems.