Universitetsparken 5, 2100 København Ø
Modern Biology produces data in unprecedented quantities, typically of a high-dimensional nature with non-trivial correlations and substantial levels of noise. Making sense of such data is one of the main challenges of our time, not least in the context of understanding human disease. My research is concerned with developing Machine Learning algorithms in this problem domain.
Currently, my group focuses primarily on problems in molecular biology, in particular in understanding the structure of biomolecules such as proteins. Our work is a mixture of (primarily Bayesian) Statistics, classic Bioinformatics, and Machine Learning.