Investigating Viral Evolution and Host Interactions through Data

I am interested in how viruses evolve and interact with their hosts to persist. I focus on building computational methods that extract meaningful patterns from large-scale sequencing and multi-omics data to better understand viral biology.

During my PhD, I worked on SARS-CoV-2 intra-host evolution, building scalable tools to refine low-frequency mutations and track signals of selection across global sequencing data. This work combined genomics, population genetics, and dimensionality reduction to better understand how SARS-CoV-2 changes within individuals and across populations.

Now, as a postdoc, I am extending this work to study integrated viral reservoirs using single-cell data from SIV-infected non-human primates. I aim to identify viral integration sites, assess their impact on host gene regulation, and test whether certain integration events drive clonal expansion.

Recently, I became interested in systems virology using epigenomic, transcriptomic, proteomic, and metabolomic data to study how hosts respond to infection. I apply bioinformatics tools that scale to large datasets, with a focus on dimentionality reduction, interpretability, and multi-omics integration.

Across these projects, I’m interested in how viruses shape and are shaped by host systems, where I use data to trace that interplay.