Stanford University
Showing 11-20 of 2,077 Results
-
Jiyoun Ha
Graduate, Stanford Center for Professional Development
BioMachine Learning Engineer @ Google. Currently focusing on efficient model training and inference.
-
Kirstin Haag
Teaching Excellence Program Designer, Teaching and Learning Hub
Current Role at StanfordTeaching Excellence Program Designer, Teaching and Learning Hub, Stanford Graduate School of Business
-
Richard Haarburger
Postdoctoral Scholar, General Internal Medicine
BioRichard Haarburger is a postdoctoral scholar in the Department of Medicine (Primary Care and Population Health) at Stanford University, working in the lab of Pascal Geldsetzer. He studies questions at the intersection of epidemiology, health policy, and applied econometrics, with a focus on causal inference in large real-world health datasets.
His current work uses quasi-experimental and survival analysis methods to evaluate how preventive interventions (e.g. herpes zoster vaccinations) affect neurological outcomes such as dementia incidence at the population level. He also develops empirical strategies for dealing with challenges common in observational health data, including treatment effect heterogeneity, incomplete outcome follow-up, and competing risks.
Richard’s broader research interests include impact evaluation methods, causal machine learning, and the health and economic consequences of new technologies. During his PhD in quantitative economics, he worked on measurement bias in health surveys, high-dimensional forecasting, and heterogeneity in technology adoption.
