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I am a final year Ph.D. candidate in the Department of Electrical & Computer Engineering at University of Arizona, USA., advised by Prof. Siyang Cao.

My research is driven by a deep passion for leveraging AI technologies in healthcare to enhance the quality of life. My research interests include:

• Radar signal processing and machine learning for human skeletal pose estimation, fall detection, and fall risk assessments.
• Healthcare technologies for diagnosing and rehabilitating motor deficits in patients, such as Alzheimer’s and Parkinson’s diseases.
• Radio Frequency (RF) systems, multimodal sensing technologies (e.g., Radar, LiDAR, Wi-Fi), and joint sensing in 6G networks.

News

2025-02: The paper “mmWave Radar for Sit-to-Stand Analysis: A Comparative Study with Wearables and Kinect” is accepted to IEEE Transactions on Biomedical Engineering.

2023-12: The paper “mmPose-FK: A forward kinematics approach to dynamic skeletal pose estimation using mmWave radars” is accepted to IEEE Sensors Journal.

2023-11: The paper “Radar-Based Fall Detection: A Survey” is accepted to IEEE Robotics & Automation Magazine.

2022-07: The paper “Stabilizing skeletal pose estimation using mmwave radar via dynamic model and filtering” is accepted to IEEE BHI-BSN-2022.