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AMSI-ANZIAM Lecture Tour, Brisbane

AMSI-ANZIAM Lecture Tour, Brisbane

Image Credit: Australian Mathematical Sciences Institute (AMSI)

2023 ANZIAM Lecturer

The AMSI-ANZIAM Lecture Tour invites a distinguished international academic in an Applied Mathematical field to speak at universities across Australia after the conclusion of the ANZIAM Conference. It includes a series of talks including Specialist and Public lectures. The tour is organised biennially by AMSI and is supported by ANZIAM.

Date: 22 February 2023
Time: 4:00–5:30 pm AEST
Venue: The University of Queensland: Building 7 (Parnell) room 222, Saint Lucia, Brisbane, QLD
Title: Aesthetics and ubiquitous applications of Markov chains

Professor Konstantin Avrachenkov
National Institute for Research in Digital Science and Technology (INRIA)

Konstantin Avrachenkov received his Master degree in Control Theory from St. Petersburg State Polytechnic University (1996), Ph.D. degree in Mathematics from University of South Australia (2000) and Habilitation from University of Nice Sophia Antipolis (2010). Currently, he is a Director of Research at Inria Sophia Antipolis, France. He is an associate editor of the International Journal of Performance Evaluation, Probability in the Engineering and Informational Sciences, ACM TOMPECS, Stochastic Models and IEEE Network Magazine. Konstantin has co-authored two books “Analytic Perturbation Theory and its Applications”, SIAM, 2013 and “Statistical Analysis of Networks”, Now Publishers, 2022. He has won 5 best paper awards. His main theoretical research interests are Markov chains, Markov decision processes, random graphs and singular perturbations. He applies these methodological tools to the modeling and control of networks, and to design data mining and machine learning algorithms.

Talk Abstract: Markov chains, mathematical models that describe sequences of dependent events, were created to make a point in a philosophical discussion and to explain the beauty of the poetry. Even though we may debate the practicality of explanations of aesthetics, it is generally accepted that Andrey Markov (1856–1922) contributed to this philosophical dispute and, in the process, originated one of the most powerful tools of applied mathematics, physics and data science.

In this talk, I first give an accessible introduction to Markov chains and in particular to singularly perturbed Markov chains. These are stochastic dynamical models with several time scales and, as such, are well suited to represent many natural and technological phenomena. In particular, I discuss the application of Markov chains and singularly perturbed Markov chains in linguistics, linked data analysis and reinforcement learning.