Applications:
Behavioral Science, Computer Science
Methodologies:
Artificial Intelligence, Databases and Data management, Machine Learning

Hamid Ghanbari

Associate Professor

Internal Medicine

Assistant Professor of Internal Medicine, Medical School

My research focuses on using digital health solutions, signal processing, machine learning and ecological momentary assessment to understand the physiological and psychological determinants of symptoms in patients with atrial fibrillation. I am building a research framework for rich data collection using smartphone apps, medical records and wearable sensors. I believe that creating a multidimensional dataset to study atrial fibrillation will yield important insights and serve as model for studying all chronic medical conditions.


Accomplishments and Awards