Jesse Gronsbell
Assistant Professor of Statistical Sciences
Cross appointed in Computer Science and Family & Community Medicine
About. I develop statistical and machine learning methods to extract reliable insights from modern observational health data.
Methodological Interests. Semi-supervised learning, weakly-supervised learning, post-prediction inference, meta-analysis.
Recent Applications. Electronic health records, biobanks, mobile health.
News.
Feb 2023.
Working on a machine learning in health project that was surprisingly unsuccessful? Please submit a lightning talk to CHIL by March 15! [more info]
Talk on curating electronic health records data for real-world evidence at the Toronto Reproducibility Workshop. [slides][recording][paper]
Talk on evaluating algorithmic unfairness in labeled data limited settings at the DSI Blitz Workshop in Computational and Quantitive Social Sciences.
Jan 2023. Happy New Year!
Teaching a graduate seminar on likelihood inference. [website]