I'm a Postdoctoral Researcher at the UCSF TECH Lab under Dr. Peter Washington, having recently completed my Ph.D. at UIC. My work sits at the intersection of human-computer interaction, AI-supported interactive systems, and human-in-the-loop design.
I'm drawn to the gap between what technology can do and what people can actually reach. I believe good systems shouldn't ask people to learn their language. They should learn to understand ours. From everyday devices to clinical care, I design and study AI that adapts to people's abilities, contexts, and needs, especially for those technology tends to overlook.
Research areas
Human-centered AI in care
Exploring how AI can support clinical communication and decision-making in ways that are safe, transparent, and grounded in human judgment.
Intent-aware interaction
Designing systems that understand what people mean, not just what they say, so they can reach what they need without technical know-how.
Understanding behavior through interaction
Studying how the ways people interact and collaborate with technology can reveal meaningful signals about cognition, health, and development.
Inclusive and accessible design
Examining how cognitive, perceptual, and experiential differences shape our relationship with technology, and designing for people it tends to leave behind.
Publications
10 peer-reviewed papers · CHI · ASSETS · UbiComp · VRST · INTERACT
Developed a Kotlin Multiplatform app delivering food safety information for expectant mothers. Implemented an LLM-based autonomous pipeline to resolve data sparsity by retrieving and synthesizing unstructured web data. Conducted iterative UX optimizations to ensure reliable interpretation of safety recommendations by non-expert users.
LLM agentsKotlin MultiplatformFastAPIUX research
Live · 2024–present
Dissertation · Phase 1 · Exploratory study
Toward a Good Design for Older Users
Qualitative investigation of how older adults struggle with mobile maps — uncovering that the core issue is feature discoverability, not motor skill or comprehension.
Think-aloudInterviewsAtlas.tin=17
ASSETS 2020
Dissertation · Phase 2 · Wizard-of-Oz
Designing a Voice Assistant for Mobile Navigation
Validated the voice assistant concept through a Wizard-of-Oz study — 88% of participants used it, and 77% of navigation failures were immediately resolved after intervention.
Wizard-of-OzVoice UIWeb appn=15
ASSETS 2020 · CHI 2023
Dissertation · Phase 3 · Controlled experiment
Exploring Effective Visual Cue Design
A/B tested four visual cue designs with older and younger adults. Found that highlighting with context or weighted zoom equalizes task performance across age groups.
A/B testingGLMMWeb appn=56
CHI 2024
Dissertation · Phase 4 · System build
Nav Nudge: Voice Assistant for Mobile UI Navigation
Built a fully working Android app using GPT-3 and Universal Sentence Encoder to interpret verbal queries and highlight matching UI features on-screen. 95% query accuracy in-the-wild.
AndroidGPT-3NLPn=10
CHI 2024
Research project · 2018–2020
myCityMeter / whatIbreathe
Android app measuring PM2.5 and ambient noise — environmental risk factors for cognitive impairment — for older adults and caregivers. Built with RESTful API and multi-sensor data pipeline.
AndroidIoT sensorsREST APImHealth
UbiComp 2018 · HCII 2020
M.Eng. research · 2015–2016
Blurry (Sticky) Finger
AR interaction technique for optical see-through displays: users point at distant real-world objects using a blurred finger and proprioception, eliminating frequent focus shifts and reducing eye strain.
3D reconstruction system for indoor crime scenes using smartphone and Kinect. Enables first-person virtual scene exploration and generates textured 3D face models from 2D CCTV footage.
Unity3DKinectOpenCVDlib
National Forensic Service, Republic of Korea
Ja Eun Yu, Ph.D.
yujaaa0219@gmail.com · jaeun.dev · San Francisco Bay Area, CA
