I am an Assistant Professor In-Residence in the Department of Epidemiology and Biostatistics at the University of California, San Francisco. My research interests include the interpretability and reliability of machine learning methods for biomedical applications, particularly those involving black-box models.
I completed my Ph.D. in Biostatistics under Noah Simon and Erick Matsen at the University of Washington. Before that, I studied computer science at Stanford and was a software engineer at Coursera.
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News
- Oct 2021: Romain Pirracchio and I have received a grant to extend our original UCSF-Stanford CERSI proposal “Safe algorithmic change protocols for modifications to AI/ML-based Software as a Medical Device”. This new project will look at the impacts of integrating real-world data. We’re excited to continue working with our CDRH collaborators Berkman Sahiner and Alexej Gossmann!
- Sep 2021:Our work on online recalibration and revision of clinical prediction models was presented at BIOP 2021.
- Aug 2021: I gave a talk as part of the ASA Statistical Learning and Data Science webinar series on deep learning! Check out the slides here.
- Sep 2020: Romain Pirracchio and I have received a grant from the UCSF-Stanford CERSI program for our proposal “Safe algorithmic change protocols for modifications to AI/ML-based Software as a Medical Device”. This grant will be done in close collaboration with Berkman Sahiner and Alexej Gossmann from the US FDA.
Tutorials and Short Courses
- Aug 2021: I joined forces again with Noah Simon and Cody Chiuzan to teach a short course on machine learning for biomedical and health data.
- Nov 2020: I taught a short course on supervised statistical learning with Ali Shojaie on November 15th at the 6th Seattle Symposium in Biostatistics. (Slides)
- Aug 2020: I taught a short course on machine learning for biomedical and health data with Noah Simon and Cody Chiuzan.