Thomas Wim Hamelryck
Associate Professor, Guest researcher
Computational and RNA Biology
Ole Maaløes Vej 5
2200 København N.
Programming Languages and Theory of Computing
Universitetsparken 5, 2100 København Ø
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.
Primary fields of research
Probabilistic machine learning, deep probabilistic progarmming, statistical structural bioinformatics