Malgorzata is an Associate Professor in Discipline of Mathematics at the University of Tasmania.
Her research interests are in stochastic modelling, applied probability, operations research, Markov-modulated models, matrix-analytic methods, and applications in complex systems in healthcare, evolution, and other areas.
Markov-modulated models are processes in which a Markov chain is an underlying driving process. Markov chains are the most important class of stochastic models in the theory of probability, due to their powerful modeling features and numerical tractability.
Markov-modulated models have attracted a lot of interest due to their applicability to a wide range of real-life systems of great engineering or environmental significance, well beyond applications in high-speed telecommunications systems, from which they were originally derived. The applications of these include ad-hoc mobile networks, the process of coral bleaching, operation of hydro-power generation, amongst other examples.
Malgorzata's contributions include two-dimensional and time-varying Markov-modulated models. She is interested in constructing models, analyzing them analytically, deriving mathematical expressions for transient and stationary performance measures, building efficient algorithms for their numerical evaluations, and applying the models in real life systems.