Erdem Murat

• Advisor: Prof. Lap-Fai (Craig) Yu

Conducted research in virtual reality, gameplay design/engineering, machine learning, and systems analysis with the aim of publishing in the top academic conferences.

• As a member of the lab, I have been able to:

• Receive mentorship from Prof. Yu.
• Collaborate with lab members.
• Access equipment and software required in research & development.
• Attend seminars, conferences, and  related events.

• Created virtual reality hubs for the  Global Co Lab to host conferences and present fieldwork addressing social issues.

• Optimized the prior build by 70% by utilizing functionalities in Blender, Spoke and Photoshop to reduce rendering workload.
• Instructed and mentored 3 teams towards developing educational and entertaining VR environments for the UN Sustainable Development Goals (SDG) Metaverse Competition

• Presented work at the United Nations Science Technology and Innovation Forum.

• Developed a comprehensive, 5-day curriculum with 30 hours of educational content to teach virtual reality development concepts to 20 students.
• Harnessed knowledge based on emerging VR technology through attending lectures, conducting research, and attending seminars & conferences to construct content from the field of VR.
• Integrated advice from the Mozilla Hubs team to further improve the quality and comprehensiveness of teaching materials.

View paper here

Proceedings of the 31st IEEE Conference on Virtual Reality and 3D User Interfaces (VR 2024), Orlando, FL, March 16-21, 2024

Ruizhi Cheng, Erdem Murat, Lap-Fai Yu, Songqing Chen, and Bo Han

View Paper Here

• Developed a system to address a limitation in VR development research and proposed a solution that improves user experience through machine learning to automate the manipulation of experience-affecting parameters in VR.
• Deployed a testing system to record the effect of parameter manipulation on user experience based on a 10-point rating scale of difficulty, fun, and stress.
• Used collected data to train a machine learning regressor the relations between game parameters and perceived difficulty with low prediction error (26%).
• Obtained IRB certificate for social and behavioral research and conducted user studies with over 50 participants