Zhiguo Li is a research staff member in Computational Health Behavior & Decision Science with IBM Research. His research interests lie in modeling the trajectories of health behavior, predicting the health outcomes, identifying and understanding the drivers, and informing intervention design by making use of multi-scale and multi-modal longitudinal and temporal data (e.g., time series). He has worked on several studies in behavior and health science, including medication adherence modeling using claims and encounter data, cognitive analytics for life coaching using the temporal wellness data, and predictive modeling of Type 1 Diabetes using the longitudinal measurement data.

Zhiguo Li obtained his PhD in industrial engineering (applied statistics) and worked as a researcher in the department of Business Analytics and Math Science, where he gained years of experience in industrial statistics, data mining, and machine learning with applications to different engineering or business processes including project management and forecasting, transportation, supply chain, and medical imaging systems, etc.