Dean — Ivan Arzhantsev
First Deputy Dean — Tamara Voznesenskaya
Deputy Dean for Research and International Relations — Sergei Obiedkov
Deputy Dean for Methodical and Educational Work — Ilya Samonenko
Deputy Dean for Development, Finance and Administration — Irina Plisetskaya
Phone: +7 (495) 772-95-90 * 12332
125319, Moscow, 3 Kochnovsky Proezd (near metro station 'Aeroport').
For a researcher in a diverse and quickly developing area of knowledge such as computer science, it is important to maintain a broad perspective and strive to understand what colleagues in related fields are studying. This requires a platform where specialists can meet and tell each other about their latest findings in a common language. Such a platform is the Colloquium of HSE's Faculty of Computer Science. This platform is a faculty-wide academic seminar designed for teachers and research staff, graduate and undergraduate students, as well as those who are interested in computer science.
Colloquium meetings are held on Tuesdays in the Faculty of Computer Science building at Kochnovsky Proezd, 3, lecture hall 205, 2nd floor.
NB: a somewhat more detailed web page is available in Russian here.
Luca Bernardinello (University of Milano-Bicocca)
Games on graphs and on trees have been used in the fields of semantics and verification. Usually, they are defined as sequential games, where a play is a sequence of moves by the players.
However, when synthesizing or analyzing distributed systems, in which events happen concurrently and the global state is not observable, this approach is not always appropriate, since concurrency is hidden in the interleaving of events. Therefore, several kinds of games in which the players can move asynchronously have been proposed in recent years. I will present an attempt to define such a game, originally conceived in order to tackle the problem of “observable liveness”, in which an agent tries to control a Petri net so that a given transition will fire over and over, assuming that only a subset of the transitions is directly controllable.
Head of vision modelling lab / HSE
Computational models in psychology and neuroscience share many algorithms with machine learning, machine vision and artificial intelligence, but the focus of the research is different. Where applied fields try to create algorithms that solve or automate a specific problem, computational modelling uses these algorithms to better understand fundamental workings of human brain and cognition. Rather than optimizing a new process, we try to simulate and understand an existing process. While computational modelling is still a growing field, there have emerged a number of contenders that perform very well in simulating various neural and cognitive processes. Diffusion models of decision making, salience models of vision and more recently deep learning models of object classification have all shown promise on their respective tasks. This talk will give an overview of a number of these models and discuss possible points of overlap with computer science and cognitive psychology.