Luca Nesterenko

The paper introduces a deep learning framework for estimating epidemiological parameters from viral sequences, achieving high accuracy and speed compared to traditional methods.

This paper develops a deep learning model to identify selective pressures on protein sites, showing it outperforms likelihood-based methods on similar data but is less effective on divergent datasets.

Phyloformer uses deep learning to quickly and accurately reconstruct phylogenetic trees from protein sequences, outperforming existing methods on simulated and real data.