I am currently a senior data scientist and a technical lead on the Sensors Data Science team at Verily Life Sciences. I have been focusing on developing machine learning models for Verily’s Study Watch applications, such as monitoring Atrial Fibrillation (AFib).

Before joining Verily, I received my PhD in Electrical Engineering from Princeton University, advised by Professor Barbara Engelhardt and Professor Kai Li. My primary research interests lie at the intersection of machine learning and digital health. I have been focusing on developing scalable and robust models for analyzing high-dimensional observational time series data from real-world Electronic Health Records (EHRs) and mobile devices.

Besides my main PhD work, I also have colloborations on a variety of research projects, such as recommending clinical actions using reinforcement learning, analyzing mobile health time series data, and reconstructing isoforms from RNA-seq data. 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.