Motivation
The challenge of representing natural processes through mathematical frameworks to capture their inherent complexity fascinates me. Developing appropriate statistical tools for these representations through the lens of Object Oriented Data Analysis is a core motivation that drives my work.
I am eager to contribute to projects where building and analyzing complex mathematical objects can enhance our understanding of pressing biological questions, especially in ecology, disease tracking and disease prevention, as well as sociological questions aimed to improving long-standing problems. My goal is to bridge meaningful biological/sociological insight with methodological innovation, enabling nuanced and data-driven perspectives on how living systems function and evolve.
Current Research
My current postdoctoral position with Dr. Amy Willis aims to build new statistical tools for the analysis of phylogenetic trees.
We introduced a continuous metric between phylogenetic trees with overlapping but non-identical leaves, reflecting the reality of evolutionary histories for transferred genes shared by some but not all bacteria and archea and providing an intuitive comparison method for these trees.
Development of quick and efficient algorithms to compute this distance, along with an R package for its implementation.
Analysis of the properties of the Sample Fréchet Mean for trees in our metric space.
Collaboration with Dr. Armeen Taeb on a new tool for tree reconstruction, employing a Poset structure to guarantee stability and a low False Discovery Rate.
Finalizing the manuscript and publishing an accompanying R package.
Publications
Published Articles
Advances in Applied Mathematics, 178.
doi.org/10.1016/j.aam.2026.103091 →
IEEE Transactions on Computational Biology and Bioinformatics, 22(2), 614–627.
doi:10.1109/TCBBIO.2025.3526422 →
AIDS and Behavior.
doi:10.1007/s10461-022-03841-z →
Morfismos, Vol. 23 No. 1.
Preprints
doi:10.48550/arXiv.2511.23433 →