Zhipeng is a principal data scientist at Geneia, working to improve health outcomes for people with chronic diseases and reduce the costs of chronic diseases through predictive modelling. His focus is creating AI models that identify people at high risk for developing chronic conditions such as hypertension and diabetes, while also helping care managers provide personalized management for high-risk patients.
Zhipeng is an experienced researcher in the fields of computational genomics, pharmacogenomics and causal inference. Before joining Geneia he was an Insight Health Data Science-program Fellow, where he created a predictive model that uses electronic health record data to identify people at high risk for developing fatty liver diseases. In his five years at Purdue University he studied how genetics factors contribute to the development of metabolic diseases and published six peer-reviewed papers in high-impact journals. Additionally, part of his Ph.D. work was published in the highly-ranked Journal of Hepatology.Zhipeng holds a Master of Science in statistics and a Ph.D. in pharmacology from Purdue University. He also earned a master’s in biochemistry and bachelor of engineering in bioengineering. When not working Zhipeng enjoys photography and playing board games.