We use evolutionary approaches to study the spread of infectious diseases. To do so, we develop and test statistical phylogenetic models, especially phylodynamic models. We are also strongly interested in understanding model limitations, adequacy, and general trustworthiness.
We thank the SciLifeLab and Wallenberg National Program for Data-Driven Life Science and the Laboratory for Molecular Infection Medicine Sweden for their generous support.
Views and opinions expressed on this site should not be construed to reflect those of any government, funding body, or other person beyond the author(s).
selected publications
- The molecular epidemiology of multiple zoonotic origins of SARS-CoV-2Science, 2022
- How trustworthy is your tree? Bayesian phylogenetic effective sample size through the lens of Monte Carlo errorBayesian analysis, 2024
- Random-effects substitution models for phylogenetics via scalable gradient approximationsSystematic Biology, 2024
- Scalable gradients enable Hamiltonian Monte Carlo sampling for phylodynamic inference under episodic birth-death-sampling modelsPLOS Computational Biology, 2024