Bring AI to Healthcare with Trust and Safety
Our lab develops state-of-the-art trustworthy AI algorithms and systems to assist clinicians in diagnosis, monitoring and personalized treatment planning, and to help individuals improve health through advanced personal health informatics.
Translational Research
We focus on deep learning frameworks that provide trustworthy, interpretable and actionable insights for practitioners in various medical specialties, and to improve personal health.
Riding Posture Asymmetry Analysis
Multi-modal AI for riding posture asymmetry analysis for people post-stroke during powered mobility
Remote Kinematic Analysis
AI-powered real-time kinematic analysis system on edge devices validated by clinical ground truth.
Latest Publications
Developing AID-PMDA: an AI-driven Power-Mobility Driving Assessment System
B. Bergo, T. Dang, J. Rogers, M. Jara, A. Raheja, N. Fullmer, E. Rosario, and T. Chen
American Medical Informatics Association (AMIA) Annual Symposium (poster), November, 2025.
Mobility Scooter Riding Behavior Stability Analysis Based on Multimodal Contrastive Learning
J. Chung, C. Zhang, and T. Chen
IEEE International Conference on Big Data (Big Data), December, 2024.
Remote Kinematic Analysis for Mobility Scooter Riders Leveraging Edge AI
T-D. Nguyen, C. Zhang, M. Gitbumrungsin, A. Raheja and T. Chen
AAAI 2024 Fall Symposium on Machine Intelligence for Equitable Global Health (MI4EGH), November, 2024.