Contact
jxu@envisionus.com
316-440-1527
Expertise And Interests
• Human-Machine Interactions, Human Factors and Driver Behavior
• Virtual Reality, Immersive Virtual Simulation Design, Development and Evaluation
• Assistance and Automation Technologies for Visually Impaired Drivers
Bosma Enterprises Research Fellow
Dr. Jing Xu is a Bosma Enterprises Research Fellow at the Envision Research Institute, working under the mentorship of Dr. Alex Bowers, an Associate Professor of Ophthalmology at Harvard Medical School and an Associate Research Scientist at Schepens Eye Research Institute of Massachusetts Eye and Ear, and Dr. Rui Ni, an Associate Professor of Psychology at Wichita State University and Director of Visual Perception and Cognition Laboratory.
Dr. Xu earned her Doctorate of Philosophy in Industrial Engineering with a concentration in human-machine interaction and driving safety research in the Intelligent Human-Machine Systems Laboratory at Northeastern University. After graduation, she has worked under the guidance of Dr. Alex Bowers as a Postdoctoral Research Fellow at the Bowers Laboratory.
Her main research interests focus on using virtual simulation technology to investigate the impact of vision impairments on driving, developing and investigating new assistance and automation technologies to support safe mobility for drivers with age-related vision loss. One of her projects at Schepens Eye Research Institute has been to develop and assess a Head Scanning Reminder Device to help drivers with Homonymous Hemianopia. Preliminary results show that this device can effectively promote early, proactive head scans to the blind side with significant positive effects on driving safety. For her dissertation research, she developed a novel networked multi-driver simulation platform, which can conduct various single-driver behavior studies, and engage multiple drivers in a shared virtual environment for real-life interaction scenarios. Enlightening studies on Connected Vehicles, Crash Avoidance Assistance Systems, driving distractions, and vulnerable road user safety were conducted by using this platform.