Dr. Li is a behavioral statistician with a joint appointment in the Department of Psychiatry & Behavioral Sciences and the Department of Epidemiology and Biostatistics. He applies the following statistical techniques in understanding complex human behaviors: social network analysis, random walk on a network using discrete time Markov chains, Bayesian hierarchical linear models, latent regression, and Item Response Theory modeling. Dr. Li is a recipient of NCI funding to use cellular phones as social network sensors to examine social network influences of smoking in young adults. This project is the first of its kind to use mobile sensing technology to study smoking behaviors in real time. Highlights of his publications include a book on behavioral research data analysis, Bayesian IRT, latent regression Rasch model, and Bayesian Latent Class Analysis. He is also actively conducting research on statistical methods that best elucidate the genetic determinants of mild cognitive impairment after chemotherapy (with Dr. Ahles, Psychiatry) and Bayesian statistical methods to examine intervention fit (with Dr. Ostroff, Psychiatry).