Finnish centre of excellence in Randomness and STructures (FiRST) (FIRST)


Main funder

Funder's project number346311


Funds granted by main funder (€)

  • 253 011,00


Funding program


Project timetable

Project start date01/01/2022

Project end date31/12/2024


Summary

Our proposal brings together leading mathematicians in Finland, including a new generation of world-class experts, to collaborate towards the advancement of the common research themes of "Randomness and Structures". Each of the three previous ICM's has seen one of our PI’s as an invited speaker. The role of the probabilistic point of view has become increasingly important during the past years. A wide range of important problems in pure and applied contemporary quantitative sciences require methods and knowledge from probabilistic methods in combination with other fields of mathematics. A key example of this is random geometry, a new, vibrant field which studies random geometrical objects that arise in classical and quantum statistical physics. Our teams have been at the forefront of the mathematical developments at the cross-road between probabilistic methods, quantum and conformal field theory, geometric and harmonic analysis which have made Finland a major international center in random geometry. Moreover, in analytic number theory the probabilistic point of view has gained increasing importance, and bringing in the latest advances in harmonic analysis will be valuable. Homogenization and general multiscale stochastic analysis are in our research ubiquitous tools whose development is also one of our pivotal interests. We are in a worldwide unique position where the particular strengths of our teams perfectly fit our tasks.
An essential part of our proposal are applications of cutting edge mathematics, building on our joint expertise and past experience. This includes functional data analysis methods together with development and analysis of adaptive probabilistic algorithms which we also envisage to apply to the analysis of probabilistic machine learning and its uses in the construction of numerical solution of rough PDEs. Another key research goal is the mathematical modelling of rock structures in view of applications to geothermal energy. We will also continue our pioneering work on 'atmospheric mathematics'. One particular goal is to improve the predictive accuracy of coagulation-- fragmentation models.
We want to sustain and develop researcher training in our fields. A broad background is more and more essential even in pure mathematics as well as openness for getting involved with applications. The gender composition of our team of PI's naturally offers role models to support equality and diversity in mathematics research.


Principal Investigator


Other persons related to this project (JYU)


Primary responsible unit


Follow-up groups

Profiling areaDecision analytics utilizing causal models and multiobjective optimization (University of Jyväskylä JYU) DEMO; 2017-2021


Related publications and other outputs


Last updated on 2024-27-02 at 02:35