Summary
I am an interdisciplinary data scientist and cancer biologist at UT Austin advancing high-throughput single-cell technologies and computational approaches to investigate cell-cell fusion and heterogeneity in cancer. I have extensive expertise in analyzing and visualizing large-scale single-cell transcriptomics data. This is complemented by over a decade of hands-on wet lab experience and a strong record of leadership in interdisciplinary research and within local communities.
Approach to science
I believe that complex patterns often emerge from simple rules. This perspective guides my efforts to develop tools to uncover the molecular mechanisms driving cellular behaviors in health and disease.
Cell-cell fusion and syncytialization as a transient cell state
While the only human cells known to naturally participate in cell-cell fusion are characterized by the maintenance of multiple nuclei, in vitro studies have observed cell-cell fusion as a transient state, resulting in single-nucleated progeny that closely resemble their parental cells. This phenomenon has been documented in cancer cells, iPS cells, and macrophages, amongst others. Based on these observations, I hypothesize that transient syncytialization may occur in the human body far more often than can currently be measured. To begin to explore this, I have developed high-throughput single-cell systems and computational approaches to identify biomarkers of cell-cell fusion in cancer.
Data Visualization
Complex data doesn’t have to look complex. I take joy in identifying meaningful patterns in high-dimensional data and transforming insights into striking visuals, making complex biological insights more accessible and impactful.