About me

My research focuses on understanding how dynamic gene regulatory networks (GRNs) control cells’ fate decisions during tissue development and regeneration. This work integrates machine learning and single-cell transcriptomics with lineage tracing and genetic perturbations to dissect biologically relevant sub-networks across embryonic tissues and stem cells. I am also interested in bridging computational predictions with experimental validations to relate cells’ distinct phenotypes with underlying mechanisms of gene regulation.

I completed my PhD in the laboratory of A. J. Hudspeth at Rockefeller University in 2024, where I was also a member of the Tri-Institutional PhD Program in Computational Biology and Medicine. My thesis research focused on the development of novel deep-learning methods for GRN reconstruction from single-cell sequencing data, and computational and experimental validations of GRN predictions across diverse cell types, including regenerating sensory cells in larval zebrafish and maturing Purkinje neurons during first-trimester neurodevelopment.

‘Day science’ employs reasoning that meshes like gears and achieves results with the force of certainty. ‘Night science’ is a sort of workshop of the possible, where hypotheses take the form of vague presentiments and hazy sensations. -François Jacob

Publications

Check out my publications on Google Scholar

Fellowships

Karolinska Institutet Nicholson Postdoc, 2025
Karolinska Institutet Nicholson Fellowship, 2022
NSF Graduate Research Fellowship Program, 2021
Graduate Fellowship, Rockefeller University, 2020 
NSF REU Program, University of Pittsburgh, 2018

Education

PhD in Computational Biology & Medicine, The Rockefeller University, 2024
BS in Molecular Biology & Applied Mathematics, Lipscomb University, 2019

Organizations

Rockefeller Student Representative Council, 2020
New York Academy of Sciences Member, 2019
Tri-Beta Biological Honors Society, 2017

The Philosopher’s Garden at Rockefeller University