Project Description

Person-generated health data (PGHD) from smartphones/wearables is invaluable to precision health, a field that uses advanced analytics to develop individual-specific health and well-being interventions. This project focuses on developing advanced analytics and validation using Person-generated health data collected from wearables, quantifying the risks of exacerbating disparities in underrepresented groups. This is an interdisciplinary team of researchers with expertise spanning engineering, AI/ML, sociology, and public health. 

Start Date

Feb 2025

Postdoc Qualifications

The postdoctoral researcher should have a degree in Computer Engineering, Applied Mathematics, Mechanical Engineering, Biomedical Engineering, or equivalent. The research requires a strong background in machine learning and artificial intelligence. 

Co-advisors

Arezoo Ardekani, Professor of Mechanical Engineering, ardekani@purdue.edu
https://web.ics.purdue.edu/~ardekani/
Alok Chaturvedi, Professor of Management, Information Systems, alok@purdue.edu

Bibliography

Chaturvedi, Ritika & Angrisani, Marco & Troxel, Wendy & Gutsche, Tania & Ortega, Eva & Jain, Monika & Boch, Adrien & Kapteyn, Arie. (2023). American Life in Realtime: a benchmark registry of health data for equitable precision health. Nature Medicine. 29. 1-4. 10.1038/s41591-022-02171-w.