About
I am a Human Factors researcher and Ph.D. student in Industrial and Operations Engineering at the University of Michigan, where I work as a Graduate Research Assistant in the Intelligence & Human Augmentation Lab (iHub) and am advised by Dr. Manhua Wang.
I hold an M.S. in Human Factors and Ergonomics from San José State University, where I previously conducted research at the Behavior, Accessibility, and Technology Lab (BAT Lab) and was advised by Dr. Gaojian Huang.
Research interests
- Human behavior modeling grounded in human factors theories and frameworks.
- Risk perception, situation awareness, and decision-making during human-machine interaction.
- Behavioral and multimodal datasets used to develop theory-based quantitative models for actionable feedback and system interventions in automated driving and intelligent mobility.
Cited by
| All | Since 2021 | |
|---|---|---|
| Citations | 96 | 96 |
| h-index | 6 | 6 |
| i10-index | 4 | 4 |
Source: Google Scholar · Updated
Featured Paper
[J1]Shared Control in Micro-Mobility: Effects of Rider Skill and Automation Levels on Subjective Well-Being in E-Scooter Use
[J3]Directional Vibrotactile Takeover Requests on a Wrist-Worn Device: Effects of Age, Pattern Type, and Urgency in Automated Driving
[C12]Toward AI Standardization: A Triadic Human-AI Collaboration Framework for Multi-Level Autonomous Mobility
Experience
Research Experience
Graduate Research Assistant, Intelligence & Human Augmentation Lab
University of Michigan, Ann Arbor. Advisor: Dr. Manhua Wang.
Behavior, Accessibility, and Technology Lab
Laboratory Manager (2024-2025) · Graduate Research Assistant (2023-2025)San José State University, San José. Advisor: Dr. Gaojian Huang.
Teaching Experience
[GSI] Graduate Student Instructor · IOE - 333 Human Factors Ergo
University of Michigan, Ann Arbor, MI · Lecturer: Manhua Wang, Ph.D.
[TA] Teaching Assistant · THEA - 1118 Visual Identity Design
National Taiwan University, Taipei · Lecturer: Kevin Lin
Service
Conference Proceedings Reviewer
Human Factors and Ergonomics Society Annual Meeting (ASPIRE); IEEE International Conference on Human-Machine Systems (IEEE ICHMS); International ACM Conference on Automotive User Interfaces (AutomotiveUI); IEEE Intelligent Vehicles Symposium (IEEE IV 2024).
Student Volunteer
International ACM Conference on Automotive User Interfaces (AutomotiveUI)
Journal Reviewer
Transportation: Planning - Policy - Research - Practice
Conference Session Co-Chair
HFES Annual Meeting - Surface Transportation Technical Group
Student Volunteer
International ACM Conference on Automotive User Interfaces (AutomotiveUI)
Publication
Grouped as a scholarly record, with journal articles, conference proceedings, preprints, and technical reports presented in a cleaner citation-first layout.
Journal Articles
[J1]Shared Control in Micro-Mobility: Effects of Rider Skill and Automation Levels on Subjective Well-Being in E-Scooter Use
Studies how rider skill and automation levels affect subjective well-being in e-scooter use, contributing to human-AI collaboration for mobility.
[J2]Advisor, Co-pilot, or Guardian? AI Role Framing and Human Decision Behavior in Automated Vehicle Takeovers
[J3]Directional Vibrotactile Takeover Requests on a Wrist-Worn Device: Effects of Age, Pattern Type, and Urgency in Automated Driving
Examines how age, vibration pattern type, and urgency affect directional vibrotactile takeover requests delivered through a wrist-worn device in automated driving.
[J4]Vibration Patterns That Persuade: A National Survey of Driver Preferences for Wrist-Worn Vibrotactile Displays in Automated Vehicle Takeover
A national survey of driver preferences for wrist-worn vibrotactile displays in automated vehicle takeover contexts.
Conference Proceedings
[C1]What Drivers Know and Think They Know During Takeover: Effects of Spatial Risk, Temporal Risk, and NDRT on Situation Awareness
Uses QASA to examine how spatial risk, temporal risk, and non-driving-related tasks shape actual and perceived situation awareness and response bias during automated-driving takeovers.
[C2]Connecting Automotive HMI Research and Practice: A Workshop on Exploring Effective Academia-Industry Collaboration
[C3]Driver-Adaptive Support Tree (DAST): From Driver Awareness to Adaptive Takeover Support
[C4]From Papers to Production: Opportunities and Challenges in Academic Automotive HMI Research Translation - An Expert Interview
[C5]Narrate-to-Sim: A Human Factors-Oriented Driving Simulator with Natural-Language-Supported Scenario Authoring
[C6]Not All Situation Awareness Is the Same: Decoding Driver Awareness with Physiological Signals
[C7]Student Research Track: Drivers' Correctness on Cue-Level Situation Awareness Probes: The Roles of Spatial Direction and Event State During Automated Driving Takeovers
[C8]Using Physiological Signals to Diagnose Driver Situation Awareness Deficits for Takeover Support in Automated Driving
Best Work in Progress
[C9]Effects of AI Role and Speech Message Design on Takeover Requests in Automated Driving
[C10]The Impact of Mental States, Scenarios, and Modalities on Informative Takeover Requests in Automated Driving
Studies how mental states, scenario context, and modality shape informative takeover requests in automated driving.
[C11]A Multi-Modal Human-AI Collaboration Framework for E-Scooters: Evaluating AI Roles in User Preference
Evaluates AI roles and user preference in a multi-modal human-AI collaboration framework for e-scooters.
[C12]Toward AI Standardization: A Triadic Human-AI Collaboration Framework for Multi-Level Autonomous Mobility
Frames multi-level autonomous mobility through a triadic human-AI collaboration model.
[C13]Comparing Static and Dynamic Vibration Cues in Wristband Haptic Feedback for Enhanced Driver Response in Automated Vehicles
Compares static and dynamic wristband vibration cues for enhanced driver response in automated vehicles.
[C14]A Survey on Perceptions of Smartwatch Haptic Feedback for Enhancing Automated Vehicle Takeover Decisions
Examines perceptions of smartwatch haptic feedback for automated vehicle takeover decision support.
[C15]Assessing Meaningful Visual and Tactile Feedback for Effective Automated Vehicle Takeover by Hearing and Non-hearing Drivers
Assesses meaningful visual and tactile feedback for hearing and non-hearing drivers in automated vehicle takeover.
[C16]Multimodal Feedback for Effective Takeover in Automated Vehicles for Hearing Impairment
Best Video Award
Explores multimodal feedback for hearing and non-hearing drivers, recognized with the AutomotiveUI Best Video Award.
[C17]The Impact of Meaningful Vibrotactile Displays on User Preferences Across Age Groups in Automated Driving
Studies how meaningful vibrotactile displays shape user preferences across age groups in automated driving.
[C18]Design Principles and Measurement Frameworks for Human-Centered AI and Human-AI Interaction: A Systematic Review
Preprints
[P1]Multimodal Takeover Requests for Drivers with Hearing Loss: Implications for AI-Enabled Communication in Automated Vehicles
Examines multimodal takeover requests for drivers with hearing loss and their implications for AI-enabled communication in automated vehicles.
[P2]Beyond Levels of Driving Automation: A Triadic Framework of Human-AI Collaboration in On-Road Mobility
Develops a triadic framework for human-AI collaboration beyond traditional driving automation levels.
Technical Reports
[T1]Mental States & Machine: Enhancing Driver Engagement in Automated Vehicles for Safer Transitions
Technical report on driver engagement, mental states, and safer automated vehicle transitions.
[T2]Insights for the Future of Car Rental and Ridesharing: Driving Behavior Across Different Levels of Automation
Report on driving behavior across automation levels for future rental and ridesharing contexts.
[T3]Insights for the Future of Car Rental and Ridesharing: Driving Behavior Across Different Levels of Automation [Research Brief]
Brief version of the Mineta report on driving behavior and traveler experience across different levels of automation.
Presentation
Lecture
2024-Present2026
Design Principles and Measure Frameworks for Human-Centered AI and Human-AI Interaction: A Systematic Review
Co-author; not presenter
2026
Effects of AI Role and Speech Message Design on Takeover Requests in Automated Driving
Presenter
2025
Assessing AI Roles in a Multi-Modal Human-AI Collaboration Framework for E-Scooters
Co-author; not presenter
Presented by Gaojian Huang
2025
Age-Driven Takeover Optimization in Automated Driving: Smart Wearables and Vibrotactile Feedback for Enhanced Safety
Presenter
2024
Comparing Static and Dynamic Vibration Cues in Wristband Haptic Feedback for Enhanced Driver Response in Automated Vehicles
Presenter
2024
The Impact of Meaningful Vibrotactile Displays on User Preferences Across Age Groups in Automated Driving
Presenter
Poster
2024-Present2026
What Drivers Know and Think They Know During Takeover: Effects of Spatial Risk, Temporal Risk, and NDRT on Situation Awareness
Presenter
2026
Using Physiological Signals to Diagnose Driver Situation Awareness Deficits for Takeover Support in Automated Driving
Presenter
Best Work in Progress
2026
From Papers to Production: Opportunities and Challenges in Academic Automotive HMI Research Translation - An Expert Interview
Presenter
2026
Student Research Track: Drivers' Correctness on Cue-Level Situation Awareness Probes: The Roles of Spatial Direction and Event State During Automated Driving Takeovers
Co-author; not presenter
Presented by Jincheng Ye
2025
Enhancing E-Scooter Safety with AI-Driven Systems: A National Survey on User Preferences for Multi-Modal Human-Machine Interfaces
Presenter
2nd Best Poster Award
2024
A Survey on Perceptions of Smartwatch Haptic Feedback for Enhancing Automated Vehicle Takeover Decisions
Presenter
2024
Assessing Meaningful Visual and Tactile Feedback for Effective Automated Vehicle Takeover by Hearing and Non-hearing Drivers
Presenter
Co-presenter: Aries Chu
Workshop
2026-Present2026
Connecting Automotive HMI Research and Practice: A Workshop on Exploring Effective Academia-Industry Collaboration
Demo & Video
2024-Present2026
Driver-Adaptive Support Tree (DAST): From Driver Awareness to Adaptive Takeover Support
2026
Narrate-to-Sim: A Human Factors-Oriented Driving Simulator with Natural-Language-Supported Scenario Authoring
2026
Not All Situation Awareness Is the Same: Decoding Driver Awareness with Physiological Signals
2024
Multimodal Feedback for Effective Takeover in Automated Vehicles for Hearing Impairment
Award
Best Work in Progress - AutomotiveUI 2026
Awarded for Using Physiological Signals to Diagnose Driver Situation Awareness Deficits for Takeover Support in Automated Driving by Wei-Hsiang Lo, Jincheng Ye, and Manhua Wang.
Rackham Conference Travel Grant - University of Michigan
Rackham Graduate School provides travel support for Wei-Hsiang Lo to present research and participate in academic conferences.
2nd Best Poster Award - HFES Western Region 2025
The HFES Western Region awarded second place to a poster presenting related research; A Multi-Modal Human-AI Collaboration Framework for E-Scooters: Evaluating AI Roles in User Preference was later developed from the same study.
Donald Beall Student Award for Engineering Accomplishment - San José State University
The SJSU College of Engineering honored his engineering and research accomplishments in Industrial and Systems Engineering.
SJSU Research and Innovation Student RSCA Fellowship - San José State University
The SJSU fellowship supported the related student-led research from which Directional Vibrotactile Takeover Requests on a Wrist-Worn Device: Effects of Age, Pattern Type, and Urgency in Automated Driving was later developed.
Best Video Award - AutomotiveUI 2024
Awarded for Multimodal Feedback for Effective Takeover in Automated Vehicles for Hearing Impairment by A. Chu, Wei-Hsiang Lo, and Gaojian Huang.