Researcher · Wearable physiological sensing

Yi Wang

王熠Wang Yi

I build wearable-compatible physiological AI — ring and wrist PPG, cross-modal cardiac waveform reconstruction, and non-EEG sleep staging — with a consistent focus on motion robustness and reliability-aware reporting for signals that have to survive daily life.

RECFIG. 01 — Continuous physiological signaturePPG · ECG · PSG
01
published dataset
Nature Sci. Data
03
papers & thesis
2026
02
interactive demos
live online

Research themes

01

Wearable PPG

Ring- and wrist-form photoplethysmography for HR, HRV, RR, SpO₂, and BP under rest, daily-life motion, and running.

02

PSG sleep staging

Cardiorespiratory and EEG/EOG-based sleep architecture modeling with compact, parameter-efficient backbones.

03

Cross-modal reconstruction

Mapping between cardiac waveforms (ECG ↔ PPG, BCG → ECG) to bridge sensor classes and exploit existing clinical datasets.

04

State-space backbones

Mamba / VMamba and other selective SSMs as a parameter-efficient methodological thread across multi-scale physiological signals.

Selected publications

  1. 01

    2026

    HealthRing: Physiology Dataset for Health Sensing on Rings

    Nature Scientific Data · published

  2. 02

    2026

    StoryEcho: A Generative Child-as-Actor Storytelling System for Picky-Eating Intervention

    ACM UIST 2026 · in submission · co-authored

  3. 03

    2026

    CITRUS: Continuous Insight into Trusted Rhythms of Universal Signals

    MPhil thesis · HKUST(Guangzhou) · defending May 2026

See all publications →

Projects & demos

More projects →

MPhil thesis · CITRUSDefending May 2026

Continuous Insight into Trusted Rhythms of Universal Signals

My thesis threads three studies on continuous physiological sensing — ring PPG for cardiovascular vital signs across rest, daily activity, and running; an exploratory ECG ↔ PPG cross-modal waveform bridge; and a compact PSG-side sleep-staging baseline — connected by parameter-efficient state-space architectures.

Read the thesis abstract →

54
participants
49.76 h
ring recordings
0.898
error-risk AUC

Get in touch

I am applying for PhD positions for 2026/27 in wearable sensing, biomedical AI, and mobile health. If my work fits your group, I would love to hear from you.

ywang183@connect.hkust-gz.edu.cn

Yi Wang · 王熠 · HKUST(Guangzhou) · 2026Building in public toward the May 2026 defense