IWFOS 2021: 23. - 25.6.2021 ONLINE PDF Tisk

The Department of Mathematics and Statistics together with Faculty of Mathematics and Physics of Charles University and the Union of Czech Mathematicians and Physicist organize the 5th International Workshop on Functional and Operatorial Statistics.

IWFOS 2021 will be held from 23rd to 25th June 2021 online, and during 3 days, the workshop will offer about 7 invited talks, 42 contributed talks and a poster session on theory, methods and applications in the vibrant field of functional data analysis from all over the world. The web page of the conference is https://iwfos2021.sci.muni.cz/

The purpose of the series of IWFOS is to highlight the major trends in different areas of functional statistics through the exchange of ideas and the promotion of collaboration between researchers from different countries. It aims at contributing to future developments of such areas. The workshop will be a platform for communication, exchange of ideas and interaction for researchers in statistics for infinite-dimensional and high-dimensional problems.


Aktualizováno Pátek, 11 Červen 2021 12:10
 
Záznam kolokviální přednášky 12.5.2021 (ZOOM): Stanislav Sobolevsky PDF Tisk

Next Colloquial Talk at our department - online ZOOM meeting.

Title:  Towards the Digital City: methods and applications of urban network analysis and AI
Speaker: Stanislav Sobolevsky

Time: Wednesday, 12 May, 2021, 4 pm.

Dr. Stanislav Sobolevsky will present his prior research as well as the project to start at our department under a recent MASH award, see the invitation link.

Abstract:
The growing scale, complexity, and dynamics of urban systems pose tremendous challenges within urban planning and operations. At the same time, the increasing pervasiveness of digital technology in facilitating urban activities generates a vast amount of data. This big urban data creates fresh opportunities to respond to urban challenges and gain an unparalleled understanding of complex urban systems. And recent network analysis and AI techniques help to address the complexity and interconnectedness of the urban data.
I will introduce the network analysis techniques used by my teams at NYU and MIT to study the spatio-temporal transactional data on human mobility and interactions, as well as their applications to smart urban planning and smart transportation solutions.
I further present the proposed cross-disciplinary research program I  look forward to implementing at MUNI: the Digital City Engine - a  unified, scalable analytic framework for multi-layered urban data and its methodological core - Urban Network AI - a novel fusion of network science and deep learning techniques. We shall discuss the methodological foundations of Urban AI as well as applications to predictive modeling and detection of patterns, impacts, and emergent phenomena in spatio-temporal networks of urban activity. 

Záznam přednášky ZDE

Aktualizováno Čtvrtek, 13 Květen 2021 11:23
 
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