Accelerating computationally-driven scientific discovery

We develop scalable methods and software that enables the study of complex biological systems using simulations and data.

Who we are

We are a scientific computing group with core competences in mathematical modeling,  machine learning, optimization, cloud computing and data engineering.

We engage both in fundamental method research in our core areas, as well as in applications of the methods with collaborators and industry partners. 

Our approach

Our projects often combine approaches from scientific computing, machine learning, cloud computing and data engineering. For example, by integrating discrete event simulation, global optimization and human-in-the loop semi-supervised learning, we develop next-generation cloud native software for model exploration  in the StochSS project.


Systems Biology

A prominent application area in our group is computational systems biology, where we seek to gain insight into the functioning of cellular regulatory systems through simulation of molecular and mechanistic processes. Stochastic models, discrete event simulation, and multiscale chemical kinetics have been particularly active areas of research.