Human–computer interaction · Sensing · Extended reality

About

I develop and evaluate sensing-based interfaces for extended reality (XR), combining signal processing, machine learning, and interactive system design. My recent work includes silent speech input from facial and head motion, alongside ongoing research on EMG-based target selection. I am particularly interested in how input models can handle signal variability and generalize beyond the users and conditions seen during training.

Drawing on human factors and ergonomics, I connect system development with user studies to evaluate performance, workload, and usability. My broader research includes context-aware MR interfaces, input evaluation, and avatar-mediated communication.

I am a Research Assistant at Kangwon National University. I received my M.S. in Data Science from KAIST in 2026, advised by Shuping Xiong.

Selected Research

Silent speech input

Speaking Without Sound

We developed a silent-speech input system using facial and head-motion signals and compared it with voice input and mid-air typing.

ACM CHI 2027 · Under review

Details

Adaptive MR interfaces

Transparency for XR Walking

We compared four MR rendering methods, including pedestrian-aware adaptive transparency, to examine reading performance and pedestrian avoidance while walking.

International Journal of Human-Computer Interaction · Under review

Details

Ongoing project

Concept illustration of a person reaching toward an XR menu, with signals from two upper-arm EMG sensors leading to the selected Photos button.

EMG-based input

EMG-Based Target Selection in XR

This project explores whether one or two EMG channels can identify the target a user reaches toward, including target positions not seen during training.

Data collection complete · Signal analysis and modeling in progress

Project overview