I am a postdoc in Debora Marks’ group in the Systems Biology Department at Harvard Medical School. My current research focuses on computational biology, statistics and machine learning. I have also spent some years doing reasearch in theoretical physics, in particular in early universe cosmology.

In biology, I develop probabilistic models of protein and genomic sequences. I am particularly interested in the ways sequencing data from across diverse organisms and within populations can inform us about the map from sequence to function and the effect of genetic variation. One of the main focuses of my current research is the identification of genetic variants associated to human disease and pathogen evolution.

EVE – Evolutionary model of Variant Effects: Explore our predictions for the propensity of pathogenicity of 36 million amino acid variants across more than 3k human disease genes at evemodel.org. And find here the code repository for “Large-scale clinical interpretation of genetic variants using evolutionary data and deep learning”.

In cosmology my work focused on the very early universe and its relation to string theory. I developed probabilistic models of inflation from string theory, by explicitly accounting for theoretical uncertainties. I also developed frameworks for computing accurate predictions of cosmological observables from fundamental physics models. Code implemetations for computing correlation functions of primordial density fluctuations generated during inflation are available through transpotmethod.com.

You can find my papers in my Google Scholar account.