Uncertainty quantification of biological/ecological models

Uncertainty quantification in biological /ecological systems involves the systematic analysis and characterization of uncertainties inherent in models and simulations of biological/ecological processes.

Due to the complex and dynamic nature of biological /ecological systems, uncertainties arise from various sources such as experimental variability, parameter estimation, and inherent stochasticity in biological/ecological  phenomena. Researchers employ sophisticated mathematical and computational techniques to quantify and propagate these uncertainties, providing a comprehensive understanding of the reliability and robustness of biological/ecological models. This approach is crucial for enhancing the predictive power of models, guiding experimental design, and ultimately contributing to more accurate and reliable insights into the behaviour of biological/ecological systems.

Our research group at Karlstad University is dedicated to the pursuit of the following objectives:

  1. Parameter estimation in stochastic models arising in biology and ecology
  2. Bayesian filtering methods for uncertainty quantification in the field of mathematical biology

Research Group Members: Associate Professor Nikos I. Kavallaris, Assistant Professor Grigor Nika

matematisk modell