Top-level researchers will present and discuss their latest results in stochastic (random) processes, active matter and pattern formation. With an increase in efficiency of numerical methods the simulations allow to tackle a wider reach of time and length scales. New methods such as machine learning approaches present novel ways to solve old unresolved problems. The discussion of this new opportunities is one of the main goals of the meeting. Everyone is warmly invited to attend and contribute their point of view to the discussions.
|10:30-10:55||Sergey Nechaev, CNRS, Paris, France, “Lamplighter Model of a Copolymer Absorption”.|
Alexander Valov, N.N. Semenov Institute of Chemical Physics of RAS, Moscow, Russia, “On Anomalous Statistics of Some Extreme Random Processes”.
|11:15-11:40||Gleb Oshanin, CNRS, Paris, France, “Spectral Content of a Single Trajectory”.|
|12:10-12:35||Aleksei Chechkin, Uni Potsdam, Potsdam, Germany, “Brownian Yet non-Gaussian Diffusion in a Heterogenous Environment”.|
|12:35-12:55||Vittoria Sposini, Uni Potsdam, Potsdam, Germany, “Mimicking Heterogeneous Diffusion with Time-Dependent Random Diffusivity”.|
|12:55-13:15||Anna Bodrova, Skoltech, Moscow, Russia, “Resetting Processes with non-Instantaneous Return”.|
|14:15-14:40||Mike Tamm, HSE, Moscow, Russia, “Geometrical Selection in Growing Needles”.|
|14:40-15:00||Saeed Osat, Skoltech, Moscow, Russia, “K-core of Complex Network”.|
|15:00-15:20||Kirill Polovnikov, Skoltech, Moscow, Russia, “Non-Backtracking Walks on Stochastic Networks and Detection of Clusters”.|
|15:20-15:40||Vladimir Palyulin, Skoltech, Moscow, Russia, “Blind Search Properties of Lévy Motions and Brownian Diffusion”.|
|16:10-16:35||Nikolai Brilliantov, Skoltech, Moscow, Russia, “Reinforcement Learning View on the Collective Motion of Animals: why they swirl and how they group”.|
|16:35-16:55||Alexander Osinsky, Skoltech, Moscow, Russia, “Low-rank Monte-Carlo Method for Temperature-Dependent Smoluchowski Equations”|