TingFang Lee



After receiving her PhD in Mathematics, Lee has worked in the field of number theory as a Post-Doctoral fellow at Brown University. She then made a career transition from pure math to data science. As a result, she enrolled in the Statistics graduate program at the University of Rhode Island where she specialized in data science and programming and especially interested in machine learning and applying advanced math tools to machine learning algorithms. 

After finishing the program, Lee joined the Networks and Causal Inference for Public Health and Education Research team at URI where she collaborates with Dr. Ashley Buchanan and Dr. Natallia Katenka. In her role, she builds novel methods and statistical models to assess the impact of interventions and risk factors on individuals embedded in networks, specifically those pertaining to HIV and illicit drug use.


Dr. Lee’s research interests include the following three areas:
1. Inventing models that conceptualize and measure health behavior interventions on social networks.
2. Studying methodologies to evaluate causal effects on network-based studies in the presence of missing data and missing data imputation techniques.
3. Developing stochastic process models for performing time series analysis on high frequency data.


MS in Statistics, University of Rhode Island, 2019
PhD in Mathematics, National TsingHua University, 2013