Human-Centered Computing in a Human-in-the-Loop Collaborative Future.
A brief overview of Nade Liang's
Previous Research
During Nade Liang's Ph.D. at Purdue, he contributed to multiple human factors and cognitive engineering projects, including but not limited to the following:
Physiological Sensing and Driver Behavior Modeling
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Ph.D. Dissertation: Automation-to-Human Transition of Control: An Examination of Pre-transition Behaviors That Influence Readiness to Take Over From Conditionally Automated Vehicles
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Physiological Sensing of Drivers' Situation Awareness in Level-3 Autonomous Driving (Using eye-tracking, electroencephalogram (EEG), skin conductance level and posture estimation)
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The Impact of Mind Wandering on Signal Detection, Semi-autonomous Driving Performance, and Physiological Responses
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The Effect of Secondary Cognitive Task Difficulty on Headway Maintenance and Perceived Workload with Lane Keeping Systems
Human-Centered Design of Autonomous Vehicles and HCI for Older Adults
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Understanding Older Adults' Need and Perception of Shared Autonomous Vehicles: Focus Group and Video-Based Time-Motion Analysis
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Effects of UI Information Structure SImilarity on Transfer of Training for Older Adult Users in Video Conferencing Platforms
