Dr. Le is an assistant research scientist at the University of Michigan Department of Health Management and Policy. Dr Le is also a member of the UM/Georgetown TCORS Center for the Assessment of Tobacco Regulations (CAsToR). Dr. Le is interested in mathematical modeling for cancer- and tobacco-related problems, and machine-learning applications in tobacco regulatory science. Dr. Le has developed mathematical models to evaluate the benefits and harms of breast cancer mammography and predict the number of white blood cells during acute lymphoblastic maintenance therapy in children. Dr. Le’s recent work focuses on employing mathematical models to quantify the burden of menthol cigarettes on public health and estimate the smoking cessation rate. Dr. Le is working on applying machine learning techniques to predict and understand smoking behaviors.
COntact
Location
Ann Arbor
Methodologies
Artificial Intelligence / Causal Inference / Graph-Based Methods / Machine Learning / Mathematical and Statistical Modeling / Optimization
Applications