I am a senior machine learning engineer on Meta’s Health and Wellbeing team. Before joining Meta, I was a senior data scientist tech lead on the Sensor’s Data Science team at Verily Life Sciences. I have experience leading projects like developing Atrial Fibrillation (AFib) monitoring for Verily’s Study Watch.

Before starting industry positions, I received my PhD in Electrical Engineering from Princeton University, advised by Professor Barbara Engelhardt and Professor Kai Li. My primary research interests were machine learning and digital health. I have driven multiple research projects, such as predicting medication effects and diseases from observational Electronic Health Records (EHRs), recommending clinical actions using reinforcement learning, analyzing mobile health time series data, and reconstructing isoforms from RNA-seq data (learn more from my publications). Before starting at Princeton, I received my MS and BS from National Taiwan University.

Please email me at lifangc.cheng@gmail.com for a PDF copy of my full CV.