Dr. Laura B. Balzer is an Associate Professor of Biostatistics at the University of California, Berkeley. Her expertise is in causal inference, machine learning, and messy real-world data. Dr. Balzer's work addresses challenges in the design and analysis of both randomized trials and observational studies, including novel approaches for semi-parametric inference, differential measurement, and complex dependence. Dr. Balzer's work is largely been motivated by ongoing collaborations in Uganda and Kenya. She is the Primary Statistician for several studies aiming to eliminate HIV and improve community health in rural East Africa (e.g., www.searchendaids.com). Overall, Dr. Balzer's work is informed by cross-disciplinary, real-world problems and aims to ensure methodological advances in academia translate into real-world impact.
- Causal inference
- Supervised machine learning
- Design and analysis of cluster randomized and pragmatic trials
- Complex measurement, missingness, and dependence
- Epidemiologic methods
- Global health
- Infectious diseases