Skip to main content
Skip to main menu

Slideshow

Shannon Quinn

Shannon Quinn
Blurred image of the arch used as background for stylistic purposes.
Assistant Professor

We study and develop in silico methods for quantifying spatiotemporal phenomena in the context of improving public health. This takes several forms: high-throughput image analysis of GFP-tagged z-stacks, machine learning to detect ciliary motion abnormalities in high-speed videomicroscope data, or applied statistics to predict and identify disease outbreaks.

Research Interests:

systems biology, bioimage analysis, data science

Other Affiliations:

Support us

We appreciate your financial support. Your gift is important to us and helps support critical opportunities for students and faculty alike, including lectures, travel support, and any number of educational events that augment the classroom experience. Click here to learn more about giving.

Every dollar given has a direct impact upon our students and faculty.