Our research focuses on designing intelligent mobile and pervasive computing systems that utilize mobile/embedded platforms and innovative algorithms. 

Key topics include

• Advancing sensing technologies by developing algorithms to calibrate and enhance sensor data accuracy.

• Building applications and systems to address the needs of diverse populations, with a focus on empowering vulnerable communities.

• Designing user-centric solutions that integrate accessibility and adaptability into real-world mobile/embedded environments.

We investigate how machine learning and AI can be optimized for mobile and IoT devices, while addressing the low-power, resource-constrained limitations of mobile and embedded platforms to enable innovative sensing capabilities. 

Our focus includes

• Developing federated learning frameworks for privacy-preserving AI on edge devices.

• Designing energy-efficient AI model training and inference methods for resource-limited platforms.

• Creating adaptive learning systems that respond effectively to dynamic mobile environments and sensing needs.

Our healthcare research aims to assist clinicians and improve patient care through intelligent systems.

Key areas include

• Designing wearable devices and hospital systems for real-time health monitoring.

• Analyzing medical data to provide actionable insights for diagnosis and treatment.

• Creating autonomous systems for managing and predicting patient symptoms.