Tetyana I. Vasylyeva

The paper introduces parallel algorithms to improve the computational efficiency of structured coalescent models for phylogeographic analysis, enabling faster and larger-scale studies of pathogen spread.

This study analyzes MPXV genomic data from NYC during the 2022 outbreak, identifying NYC-specific lineages and estimating multiple infections, while highlighting gaps in epidemiological-genetic concordance.

This paper introduces a gradient-based Hamiltonian Monte Carlo sampler for efficient inference in episodic birth-death-sampling models, showing significant computational improvements over Metropolis-Hastings methods.

The paper detects and characterizes the SARS-CoV-2 lineage B.1.526 in New York, showing its rapid growth and potential impact on neutralization.