Mathieson Lab Website
We are a computational lab focusing on developing machine learning algorithms for biological data. Currently we are working on inference tasks related to natural selection and demographic inference, as well as generative models for genomic data from humans, mosquitos, and other species.
Current Projects
Generative models for mosquitos
We are applying generative models to Anopheles gambiae mosquitos from Africa to learn about their evolutionary history, specifically migration between populations for the purpose of understanding insecticide resistance.
Interpretability
We are working on interpretability approaches for machine learning methods in population genetics, including GANs and CNNs.
Transformers
We are working on transformer and hybrid-style models for a range of tasks, including introgression inference and long-range dependency prediction.