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.
