The work
At the University of Michigan's Eisenberg Family Depression Center I lead the architecture and database design for a common data model that supports mobile, wearable, and sensor data in research, covering devices such as Fitbit, Apple Watch, Garmin, and continuous glucose monitors as well as survey data. I serve as principal architect for the integration of mobile data pipelines with the institution's data warehouse, built on Oracle and Pentaho, and I consult across the university on infrastructure, technology selection, and good practice for mobile technologies in research.
Results
I was the architect for a reusable institutional mobile data pipeline that the central health IT group built, piloted, and used to onboard three longitudinal, international studies, and I stayed on as a technical consultant for the implementation team. A Fitbit sleep-data automation I developed is used by more than fifteen research studies at several universities, and I co-authored a 2025 paper in the journal SLEEP describing the methods (read the article, DOI 10.1093/sleep/zsae290).
Related work
I lead the Mobile Data Experts Network, a community of practice for research teams working with mobile data. I have led three five-member student teams that built research and operational applications, including TrackMaster, a research-center membership and CRM system, and MiNap, an Apple Watch sleep-diary app. I also established a health research knowledge base with more than one hundred articles and the center's open-source code on GitHub, including Extractium.
This overview draws on the professional experience listed in my résumé.