Welcome to the homepage of Thomas Hamelryck, a researcher at the University of Copenhagen with a full professor position in High dimensional biological data analysis / Machine learning shared at the Department of Biology (Section for Computational and RNA Biology, SCARB) and the Department of Computer Science (Programming Languages and Theory of Computation section, PLTC).

I am a specialist in Bayesian modelling and probabilistic machine learning. Currently, my research mostly focuses on probabilistic machine learning applied to protein structure prediction and protein evolution. I am particularly interested in the use of deep probabilistic programming, making use of the deep probabilistic programming languages Pyro and Numpyro, and the application of directional statistics to represent non-Euclidean data. My group also contributes to the development of Pyro and Numpyro.

I have published my research in journals such as PNAS, PLoS Computational Biology, Bioinformatics and Molecular Biology and Evolution, as well as in top AI conferences such as ICML and ICLR. A deep probabilistic model based on my research is currently used for multivalent vaccine design by the Danish AI-driven biotech company Evaxion. I am also the author of the Bio.PDB module of Biopython, a widely used open-source library for computational structural biology.

Picture credit: Erika Svensson

Thomas Hamelryck


Department of biology
Section for computational and RNA biology (SCARB)
Ole Maaløes Vej 5
DK-2200 Copenhagen N


Department of computer science
Programming languages and theory of computation section (PLTC)
Universitetsparken 5, HCØ, building B
DK-2100 Copenhagen Ø

University of Copenhagen

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