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Julia Olivieri
Julia Olivieri
I’m Dr. Julia Olivieri, Assistant Professor of Computer Science at the University of the Pacific. My research lies at the intersection of computer science, biology, and statistics. Specifically, I develop algorithms to perform large-scale, rigorous analysis of RNA sequencing data. In 2022, I graduated with my PhD from Stanford University’s Institute for Computational and Mathematical Engineering with a thesis on splicing analysis in single-cell RNA sequencing data.
My passion for teaching is what drove me to become a professor. I am committed to using inclusive teaching practices to make the most out of every learning experience, whether it be online, asynchronous, or in-person. I design my courses with the goal of making every student successful, regardless of their starting point. I particularly enjoy introducing students to new subjects, with a focus on courses related to discrete math, data analysis, and computational biology.
Ph.D., Computational & Mathematical Engineering, Stanford University, 2022
M.S., Computational & Mathematical Engineering, Stanford University, 2022
B.A., Mathematics, Oberlin College, 2016
B.A., Biology, Oberlin College, 2016
- Single-Cell RNA Sequencing
- Differential Alternative Splicing
- Statistical Methods in Biology
- Discrete Mathematics and Algorithms
Recent Publications
JE Olivieri*, R Dehghannasiri*, J Salzman. The SpliZ generalizes 'percent spliced in' to reveal regulated splicing at single-cell resolution. Nat Methods. (2022) 19(3):307-310. doi: 10.1038/s41592-022-01400-x.
R Dehghannasiri*, JE Olivieri*, A Damljanovic, J Salzman. Specific splice junction detection in single cells with SICILIAN. Genome Biology. (2021) 22, 219. doi: 10.1186/s13059-021-02434-8.
JE Olivieri*, R Dehghannasiri, PL Wang, S Jang, A de Morree, SY Tan, J Ming, AR Wu, Tabula Sapiens Consortium, SR Quake, MA Krasnow, J Salzman. RNA splicing programs define tissue compartments and cell types at single-cell resolution. eLife. (2021) doi: 10.7554/eLife.70692.
