ORCID Identifier(s)


Graduation Semester and Year

Spring 2024



Document Type


Degree Name

Doctor of Philosophy in Computer Science


Computer Science and Engineering

First Advisor

Ming Li


With the rapid advancements in computer science, electronics, optics, and related fields, virtual reality (VR) gradually penetrates into our daily lives, and is predicted to become a core technology in the near future. Despite its potentials, however, existing designs and solutions for VR applications remain at the infant stage, introducing limited usability and efficiency for real-world users. Besides, the increasing prevalence of VR presents new security and privacy threats due to the vast amount of information stored in or accessible through VR devices. To bridge this gap, we exploit and combine techniques from computer science and human biology, as well as other related domains, to enhance security, usability, and efficiency of these novel applications.

In the dissertation, we investigate the emerging security and privacy threats of existing VR systems, propose novel mitigation schemes, and develop new techniques to improve user experience in emerging VR applications. Our contributions are mainly threefold. First, we introduce novel user authentication schemes on VR via a secure and convenient visual channel. Specifically, we leverage the customized blink patterns and the biometric pupil variations to identify legitimate users, which is deployable for commercial VR devices. We further enhance this work by exploiting the phenomenon of auditory-pupillary response and introducing an effort-free biometric authentication scheme for VR devices, which outperforms all state-of-the-art solutions. Second, we propose to harness users' ocular behaviors to enable accurate quality of experience (QoE) assessment for 360-degree videos, by modeling these cues into a graph and applying graph learning techniques to extract hidden information in predicting the QoE score. Third, we build a novel video recommender system for VR users leveraging additional insights from users' physiological signals to learn their preferences and interests and make corresponding recommendations.


virtual reality, security, user authentication, QoE, recommender system, human-centered computing


Computer and Systems Architecture | Other Computer Engineering


Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.



I would like to express my deepest gratitude to my Ph.D. supervisor, Prof. Ming Li, as my foremost acknowledgment. Her exceptional guidance, tremendous support, and invaluable insights have been instrumental in shaping both my academic journey and personal growth. Prof. Li's profound knowledge and extensive experience have served as a beacon leading me through the challenges of my career. The privilege of learning from her is a treasured gift that I will carry with me.

I extend my heartfelt appreciation to the members of my dissertation committee, Prof. Yonghe Liu, Prof. Jia Rao, and Prof. Dajiang Zhu, for their constructive feedback and suggestions that significantly contributed to the refinement of my research and for all the assistance in different stages of my Ph.D. study.

I am thankful to a remarkable group of friends and colleagues who offered unconditional help and mental support, and the family-like environment we created together. Special gratitude goes to Srinivasan Murali, Chaowei Wang, Youngtak Cho, Mingyan Xiao, Wenqiang Jin, and Tianhao Li, for their steadfast companionship and contributions. Our shared experiences, countless discussions, and cherished memories have enriched this endeavor beyond measure.

I would also like to thank the University of Texas at Arlington for providing the resources and facilities essential for conducting my research. Additionally, I am grateful to the staff and faculty members who have offered assistance whenever needed.

Lastly, but most importantly, I would like to thank my parents, my wife, and other family members, whose love, encouragement, and understanding have provided the strength and motivation needed to sail through challenges in academia and life. Thank you for being my pillars and cornerstones and for instilling in me the values of perseverance and resilience. This achievement is as much yours as it is mine.

Available for download on Wednesday, May 13, 2026