What I work on
Measure meaningful change
Turn smartphone, wearable, and self-report data into measures of clinical change and near-term risk. Connect predictive models with psychometrics and longitudinal analysis.
Measurement and modeling →Learn when and for whom to intervene
Use randomized experiments to evaluate intervention components, timing, and differences in response—and translate those findings into personalization rules.
Trials and adaptive interventions →Build methods others can use
Develop open-source statistical software and examine how measurement quality and analytic choices affect the reliability of machine learning results.
Software and model evaluation →Research leadership · ARPA-H EVIDENT
Measuring rapid clinical change in behavioral health
I lead a multidisciplinary program combining wearable, smartphone, video, and momentary-assessment data. As Principal Investigator, I designed the protocol and measurement stack and lead the vendor, data-security, and study-governance work.
- $6.6M
- ARPA-H award
- 20
- Team members
- 2026–2028
- Ongoing program
Background
I am a Research Associate Professor at the Center for Healthy Minds, University of Wisconsin–Madison, and previously served on the faculty at Notre Dame. I received my PhD in quantitative psychology from USC in 2017.
My research spans suicide prevention, depression and anxiety, and digital well-being, with additional collaborations in eating disorders and cognitive aging.
I co-authored Machine Learning for Social and Behavioral Research (Guilford, 2023), which received the Society of Multivariate Experimental Psychology’s 2025 Barbara Byrne Award for Outstanding Book. My work spans applied digital-health studies, statistical methodology, and open-source research software.
Contact
I’m interested in industry data science and research roles in digital health, measurement, and experimentation.
For university correspondence: jacobucci@wisc.edu.