Tatjana’s research lies at the interface of theoretical computer science and mathematical modelling. Her favourite models are probabilistic, and her favourite application are biological systems. A common thread in Tatjana’s research is the combined use of formal methods (such as model-checking, SAT solvers, automated reasoning in general) and mathematical modelling (such as Markov chains, model reduction, statistical inference, machine learning), as well as the domain-specific modelling languages and theories (such as rule-based modelling, stochastic chemical kinetics). Tatjana’s recent interests include data-informed and learning methods, targeting explanatory models of collective behaviour.

See Tatjana’s research profile on DBLPGoogleScholar, ORCID.