Ubiquitous AI for Health

Afsaneh Doryab
UVA SIE & CS

Time: 2025-09-24, 12:00 - 13:00 ET
Location: Rice 540 and Zoom

Abstract

Harnessing data streams generated by widely used devices, such as smartphones, wearables, and embedded sensors, allows AI algorithms to continuously model, detect, and predict people’s biobehavioral and social states. These algorithms can then use the resulting models to deliver personalized services, recommendations, and interventions. However, this capability also introduces new technical challenges related to data collection, processing, algorithm development, modeling, and interpretation. In this talk, I will discuss my research approaches to address some of these challenges in the context of health and wellness applications. I will demonstrate how we leverage multimodal mobile data streams to model aspects such as circadian rhythm variability. Additionally, I will describe how we integrate biobehavioral models to create innovative strategies, including music melodies designed for personalized health status communication.

Bio: Afsaneh Doryab’s research is at the intersection of ubiquitous computing, AI, HCI, and health. I work on computational modeling of human behavior (incl. Activity Recognition) from data streams collected via mobile, wearable, and embedded sensors.

For more information, please visit Human-AI Technology Lab (HAI).