Advanced Analytics in Precision Health
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 Data
As soon as possible.
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
M.K. Maruhamuthu et al.Trends in Biotechnology, 38 (10), 1169-1186, 2020.
M.K. Maruthamuthu et al. Microbiology Open, 9 (11), e1122, 2020.
M. Boodaghidizaji et al. Microbiology Open, 11 (6), e1336, 2022.
T Kim et al. Sensors and Actuators B: Chemical 420, 136438, 2024.