San Francisco Bay Area
I'm a machine learning researcher at Genentech broadly interested in facilitating trustworthy AI-guided scientific inquiry and decision-making. My current work tackles this goal through the lens of uncertainty quantification methods, and is particularly motivated by problem settings that arise drug discovery and clinical decision-making. Website: https://clarafy.github.io/
Machine learning methods for data-driven design. Advised by Jennifer Listgarten & Michael Jordan.
Designed and conducted biologging field experiments in Monterey Bay, CA. Developed supervised learning methods to characterize novel in situ behavioral patterns. Supervised by Kakani Katija.
Developed regularization schemes for suppressing chaotic dynamics in recurrent neural networks. Contributed to deep learning approach for taxonomic identification of genetic reads. Supervised by David Sussillo and Mark DePristo.
Developed new matrix decomposition method for uncovering networks in whole-brain imaging data, or more generally in time-series data. Analyzed both simulated and real neural data. Advised by Jeremy Freeman.