Afsaneh Doryab

Afsaneh Doryab is an Assistant Professor of Data Science (by Courtesy), Systems Engineering, and Computer Science at the University of Virginia. She is affiliated with the School of Data Science, Department of Systems and Information Engineering, and Department of Computer Science. Her research bridges machine learning, data mining, and human-computer interaction to model human behavior using passively collected sensor data from mobile and wearable devices.

• Education: Ph.D. and M.Sc. in Computer Science from the IT University of Copenhagen.

Her work focuses on computational modeling of biobehavioral rhythms to detect mental health changes (e.g., depression, bipolar disorder), predict physical symptoms (e.g., surgical recovery, cancer treatment), and enhance wellbeing through context-aware systems. She develops AI-driven tools for circadian-aware scheduling, emotion-aware music, and multimodal sensor analysis. Her recent publications highlight advancements in reinforcement learning, sonification, and smartphone-based nutritional assessment.

Her research aligns with interdisciplinary efforts at the University of Virginia Environmental Institute, connecting data science, health informatics, and social good initiatives. Key methodologies include longitudinal data analysis, temporal modeling, and personalized machine learning frameworks. Grants like CHS: Small and HCC: Travel support her work in computational health solutions and academic collaboration.

As an active contributor to ubiquitous computing and health informatics, she leads projects on victim tagging optimization, circadian-aware systems, and community-driven peer-to-peer economic exchange. Her lab’s outputs range from wearable sensor applications (e.g., BeWell+) to clinical activity recognition tools for operating rooms and hospitals.