Applied Mathematics

Applied mathematics is a huge field where mathematical methods are applied in various areas of human activity. We are involved namely in probability theory, applied statistics, data and analysis, calculus of variations, optimization theory, continuum mechanics, and econometrics.

Selected Projects

Estimation of Unknown Source of Atmospheric Release

Estimation of Unknown Source of Atmospheric Release

Monitoring airborne radioactivity involves determining the temporal profile and source characteristics of the release. While the location of the release is often known, the temporal profile and total quantity of the released substances are typically uncertain or only partialy known.

Taming the Tail Risks in Markets with Data-Driven Methods

Taming the Tail Risks in Markets with Data-Driven Methods

We focus on the development of new methods that allow identification of tail risks in financial markets from possibly large datasets using data-driven method.

Dynamics of Energy Prices and Uncertainty

Dynamics of Energy Prices and Uncertainty

The dynamics and uncertainty of energy and electricity prices are critical because they directly impact economic stability, policy-making, and investment decisions.

Bayesian Networks

Bayesian Networks

A Bayesian network is a model that is based on probability theory and uses graphs to model relationships between variables.

The Brownian Net

The Brownian Net

In probability theory, the Brownian net is a continuum object that describes the scaling limit of coalescing and branching random walks.

Tensor Decompositions

Tensor Decompositions

A tensor of order N is a data structure that generalises vectors (order one) and matrices (order two). A color picture is an example of a tensor of order 3 and a video sequence is a tensor of order 4.

Vortex Hunting

Vortex Hunting

The detection of vortices, ripples and other singularities in a flowing liquid or gas has been the focus of attention of engineers and mathematicians for many decades.

Dynamic Decision-Making Theory

Dynamic Decision-Making Theory

This research aims to develop a rational theory of dynamic decision-making under uncertainty, providing a solid foundation for enhancing decision-making processes in both human and technological agents.