Human–Intelligent Systems Interaction
Understanding how people and intelligent systems share information, control, and responsibility.
Human-aware
- Mental States
- Trust
- Wellbeing
Intelligent Systems
- Automated Vehicles
- Smart Office
- Smart Home
Behavior, Accessibility & Technology Lab
Intelligent systems that adapt to people—in real time.
We develop and evaluate human-aware, accessible, and adaptive interfaces for mobility, work, healthcare, education, and embodied AI.
Human–AI collaboration
Embodied intelligence in motion
Three AI roles offer different ways to share responsibility: advising a person, acting alongside them, or intervening when protection is needed.
The workstation below brings those roles into an everyday environment.
Explore the triadic frameworkHuman–AI collaboration
SenseActAdvisor AICo-pilot AIGuardian AIHuman + AISharedresponsibility
Explore human–AI interaction
An adaptive workspace
An interactive illustration of BAT Lab’s human–AI interaction concept: the same workspace responds differently when AI advises, shares control, or intervenes. Try a human state and an AI role to see the difference.
Adaptive workstationAdvisor · recommendation
DistractedSimulated estimate
AI role
Workspace
Try a state
AI role
A short stretch or a coffee break could be a useful pause.
Advisor offers a suggestion. The choice stays with you.Drag to see the light change across the desk and room.
Illustrated settings only. The airflow visual shows your selected scent.
Demo break0:15Only the illustrated screen is paused.
Research areas
We study how people work with intelligent systems, how technology can support different needs, and how interfaces can communicate information effectively.
Assistive Technology & Accessibility
Designing technology across age, ability, sensory function, cognition, and mobility.
Aging and Disability
- Non-chronological age
- Cognitive differences
- Hearing loss
- Mobility limitations
Assistive Technology
- Mobility
- Smart workplace
- Healthcare robotics
- Personalized education
Adaptive Human–Machine Interfaces
Adapting how intelligent systems communicate according to the user and real-time context.
Multimodal HMIs
- Visual Display
- Auditory Display
- Tactile Display
AI-Driven
- Adaptive
- Real-time
- Wearable
Methods across the program
- Human experiments & co-design
- Knowledge-grounded AI agents
- Multimodal sensing & wearables
- Interpretable machine learning
- Simulation & digital twinsIn development
Current directions
Active · under development
Responsibility handoff
We are developing a human-centered account of how responsibility can move between people and role-adaptive AI as readiness, risk, and uncertainty change.
Collaboration framework
Triadic human–AI collaboration
Advisor, Co-Pilot, and Guardian roles offer a practical language for studying how assistance should change across situations.
Open the frameworkResearch in development
Physical and embodied AI
We are extending human-centered AI from communication on a screen to systems that sense and act in mobility, work, health, and everyday environments.
See the research areasPublications and news
Selected papers and updates from BAT Lab.
Selected publications
Evaluating an AI-enhanced power wheelchair obstacle alert system: Effects of multimodal warning design on warning-response behavior
Tang, S., Shah, A., Gawai, A. S., Huang, S. Y., Liu, G., Xie, J., & Huang, G.
Read publicationDirectional vibrotactile takeover requests on a wrist-worn device: effects of age, pattern type, and urgency in automated driving
Lo, W. H., & Huang, G.
Read publicationLab news
BAT Lab and collaborators contribute 11 papers to the HFES ASPIRE 2026 proceedings.
The papers examine human–AI collaboration, personalized driving alerts, wheelchair interfaces, wearable displays, and evidence synthesis. Together, they connect interface design and AI methods with human-centered evaluation across mobility, health, and research practice.
Read lab newsBAT Lab received a USDOT award for role-based AI alerts and wearable interfaces.
Led by Dr. Huang as sole PI, the 2026–2027 project examines role-based human-centered AI alerts, novel wearable sensors, and multisensory cues.
Read lab newsDr. Huang received early tenure and was promoted to Associate Professor at San José State University.
The promotion and tenure take effect August 17, 2026.
Read lab newsWhere our research is cited
Explore the affiliation countries of publications that cite the lab’s verified body of work.
Research support and collaboration
Our work involves public agencies, universities, foundations, and industry partners.
Beyond BAT Lab
Human factors literature
Human Factors Daily is a free reading resource featuring recent papers published by researchers outside BAT Lab.
Free literature resource
Human Factors Daily
Human Factors Daily is a curated guide to recently published work across human–AI collaboration, intelligent mobility, accessibility, adaptive interfaces, and embodied AI. New literature is scanned every Monday and Thursday. High-confidence papers are added automatically, and pending papers are checked again as source information becomes available.
Research from outside BAT Lab.These papers are not BAT Lab publications. They were written by researchers outside the lab and are shared as a free resource for learning and study.
Explore the latest researchLatest in the collection
Intelligent MobilityWhen Automated Vehicles Cannot Retaliate: Driver-Initiated Takeover Under Aggression in Mixed TrafficIntelligent MobilityTo Takeover or Not to Takeover? The Role of Drivers’ Trust in Influencing Time Spent in Manual Versus Automated DrivingCollaborate with BAT Lab
Human factors and UX studies, emerging-technology education, research visits, and applied collaboration.
Explore collaboration