Research

Research Experience & Key Projects

Research Interests

Wearable Health Sensing Biomedical Signal Processing Machine Learning Deep Learning Computer Vision Clinical Validation Neuroimaging Brain-Computer Interface

Current Research at Samsung Research America

Staff Research Engineer II | Digital Health Lab | 2019 – Present

Leading AI-driven innovation at the intersection of wearable sensing and real-world health monitoring.

Cuffless Blood Pressure Monitoring

Led ML-based BP estimation using ear-worn PPG and inertial sensors. Directed hardware prototyping, co-designed clinical protocols, and partnered with CROs for multi-device validation.

Contactless Vital Sign Monitoring

Developed AI models to estimate heart rate, respiration, and SpO2 from facial video. Recognized as top-performing solution with product roadmap adoption.

AFib Burden Estimation

Led smartwatch-based atrial fibrillation monitoring from data collection to algorithm delivery. Published cover-featured study in IEEE JBHI (2023).

Advanced Bio-sensing Earbuds

Spearheaded transcranial vagus nerve stimulation in earbud form factor for stress detection and neural intervention.


Ph.D. Research

Rutgers University | Integrated Systems and NeuroImaging Laboratory | 2013 – 2018

Advisor: Professor Laleh Najafizadeh

Developed computational methods for predicting behavior from neuroimaging data:

  • Visibility Graph Analysis: Novel methods for decoding cortical brain states from widefield transcranial imaging
  • Functional Near-Infrared Spectroscopy (fNIRS): Dynamic time warping-based averaging frameworks for brain imaging studies
  • Fractality Analysis: Characterization of fNIRS signal dynamics using visibility graph methods
  • Multimodal Neuroimaging: Optimal electrode/optode configuration for EEG-fNIRS experiments

Impact & Recognition

  • 45+ publications at top-tier venues (IEEE, ACM, OSA)
  • 15+ patents filed in wearable health sensing
  • IEEE JBHI Cover Feature (2023) for AFib research
  • Multiple Samsung company-wide awards for innovation in health sensing and biosignal foundation models