Research

AI for Pediatric Acoustic Health

Artificial intelligence has the potential to transform how respiratory and vocal sounds are used to support pediatric healthcare. My research focuses on developing AI-enabled methods that analyze infant cries, lung sounds, and other physiological acoustic signals to provide objective, non-invasive health assessment. 

By combining biomedical signal processing, machine learning, and clinical collaboration, our goal is to create practical tools that assist parents and healthcare professionals in the early recognition of respiratory diseases and other pediatric conditions.

Current research includes AI-assisted respiratory sound analysis, infant cry interpretation, smart stethoscope technologies, and edge-computing solutions designed for use in hospitals, outpatient clinics, and home environments. This interdisciplinary research seeks to improve healthcare accessibility while providing students with opportunities to work on clinically relevant AI technologies.

Intelligent Acoustic Sensing and Active Noise Control

Many biomedical sensing systems operate in environments where background noise significantly reduces measurement quality. My research investigates adaptive signal processing, active noise control (ANC), and intelligent acoustic sensing technologies that improve signal quality before higher-level analysis is performed. Applications have included neonatal intensive care units (NICUs), smart patient-bed environments, wearable sensing systems, and intelligent acoustic monitoring.

By integrating adaptive filtering, virtual sensing, embedded systems, and real-time digital signal processing, this work aims to create robust sensing platforms capable of operating under challenging real-world conditions. These technologies provide the engineering foundation for reliable AI-based biomedical acoustic analysis and other intelligent sensing applications.

Biomedical Innovation and Technology Translation

A central goal of my research program is translating engineering innovations into technologies that improve healthcare. My work spans the complete innovation pathway—from identifying unmet clinical needs and developing engineering solutions to collaborating with clinicians, protecting intellectual property, and exploring commercialization opportunities.

 Previous research has contributed to an FDA-cleared neonatal medical device, multiple patents, NSF-supported translational research, and ongoing collaborations with hospitals, industry partners, and technology transfer organizations. Beyond developing new technologies, I am committed to mentoring students in innovation, interdisciplinary collaboration, and entrepreneurship so they can experience how engineering research can create meaningful impact beyond the laboratory.