My research lies at the intersection of formal verification, machine learning and cyber-physical systems control. I work in large part on applications in healthcare because the problems are extra hard, data extra terrible, and humans extra fun to work with, but my interests are broad and past applications have ranged from ecology to autonomous aircraft.
Within this space, I focus on three interconnected areas: (i) learning reliable, data-driven models under biased data (ii) designing verifiably safe control and decision support systems and (iii) increasing accessibility and adaptation of clinical technologies. In slightly less technical terms, I work on making autonomous medical devices & systems safe, personalized, and easy to use.
Taisa received her PhD in Computer Science and Interdisciplinary Quantitative Biology from the University of Colorado Boulder, under the advising of Dr. Sriram Sankaranarayanan and clinical mentorship of Dr. Gregory Forlenza. She also holds an MSc in Applied Mathematics from the University of Colorado Boulder, and a BA in Mathematics and Art from St. Olaf College.
Before joining Galois, Taisa was an NSF/CRA Computing Innovation (CI) Fellow at Oregon Health & Science University, and Adjunct Assistant Professor at Portland State University. She previously held research appointments at a range of institutions including the University of Minnesota, University of Virginia Center for Diabetes Technology, and Microsoft Research.
Taisa loves dogs, art and anything outside.