Xianglian is a principle data scientist at Geneia, bringing broad experience in healthcare and pharmacy to the team. Her focus is AI models that predict who is most likely to need specialty drugs in the next 12 month based on the past medical history using claims data. She is also a major contributor to our inpatient probability model. Xianglian is passionate about using leading-edge data science to make pharmaceuticals safer and more accessible. She’s specifically interested in building new AI models to predict drug safety in elderly populations, such as Medicare.
Prior to Geneia, Xianglian worked as a pharmacist in the University of Vermont Health Network-Central Vermont Medical Center to help low-income patients get prescription drugs. As a data science fellow at Insight Health Data Science Program, she created machine-learning algorithms to help a start-up pharmacy predict drug demand, optimize drug inventory and reduce costs.
Xianglian holds a PhD in biology from the University of Vermont and a pharmacy degree from Shanghai Medical University (now Fudan University, School of Pharmacy). She’s studied clinical pharmacology, pharmacokinetics/pharmacodynamics, drug discovery and drug development.
Xianglian enjoys exploring new things and skiing is her favorite sport.