Daniel Lizotte
Associate Professor
Professor Lizotte's research aims to adapt and improve reinforcement learning, machine learning, and statistical techniques so they can be applied to new sources of health data, and can in turn provide stakeholders with the best available evidence for non-myopic health decision making. He is particularly interested in problems involving multiple outcomes, causal inference, and outlier detection in the domains of public health and primary health care.
Support Staff
Margaret Lomotan
lomotam@mcmaster.ca
