I am an Assistant Professor in the Department of Epidemiology and Biostatistics at the University of California, San Francisco and the UCSF-UC Berkeley Joint Program in Computational Precision Health. 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.
- Apr 2023: Harvineet Singh will be joining as a postdoctoral researcher in the lab in July! We’re really excited to have him!
- Nov 2022: Big news! Our grant proposal on developing diagnostic tools for ML algorithms has been funded by PCORI! See the project description here.
- Nov 2022: Thank you to SER digital for the opportunity to discuss the intersection of ML and epidemiology! Slides are here.
- May 2022: Our paper “Clinical Artificial Intelligence Quality Improvement: Towards Continual Monitoring and Updating of AI Algorithms in Healthcare” is published in Nature Digital Medicine! Check it out here.
- Apr 2022: I gave a talk at the Biometrics Journal Club on the statistical considerations when regulating ML-based medical devices that evolve over time. The talk is based on our 2021 Biometrics paper “Approval policies for modifications to machine learning-based software as a medical device: A study of bio-creep”. Slides are here.
- 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
- June 2022: I co-taught the Columbia ML bootcamp with Noah Simon and Cody Chiuzan for the third time!
- 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.