Wearable Ultrasound Sensing for AR/VR Platforms

Overview

As a Research Scientist Intern at Meta Reality Labs Research, I contributed to the development of wearable ultrasound sensing systems targeting next-generation AR/VR input modalities. The work spanned transducer array design, multi-channel signal processing, and real-time performance optimization.

Key Contributions

• Designed and prototyped high-performance wearable ultrasound transducer arrays optimized for body-worn form factors.
• Developed Doppler-based motion rejection algorithms to suppress motion artifacts in dynamic wearable environments.
• Built SVD-based signal filtering pipelines for clutter suppression and SNR enhancement.
• Created imaging and sensing validation tools for system-level feature verification and benchmarking.
• Led sensor characterization and beamforming parameter optimization using MATLAB/Python.

Methods & Tools

• Multi-channel ultrasound system optimization
• Doppler signal processing and motion artifact suppression
• SVD-based spatiotemporal filtering
• MATLAB and Python for algorithm development
• Cross-functional collaboration (hardware, firmware, algorithm teams)

Context

This work was conducted under the supervision of Dr. Francesco Marsili at Meta Platform Inc., Pasadena, CA (May–November 2025).