Research
Advancing Human-Computer Interaction through innovative Extended Reality technologies
PhD Thesis
Enhancing User Experience in Extended Reality through Predictive Hand Gesture Tracking
My doctoral research investigates how predictive algorithms and proactive feedback can enhance user experiences in Extended Reality environments. The work focuses on reducing perceived latency and improving interaction naturalness through anticipatory systems that predict user intentions before physical actions are completed.
Research Objectives
- Develop predictive models for hand gesture tracking in VR/XR environments
- Investigate the role of proactive haptic feedback in shaping user perception
- Evaluate the impact of predictive interactions on user experience and task performance
- Establish design guidelines for implementing predictive interfaces in XR systems
Methodology
- User studies and controlled experiments
- Quantitative and qualitative data analysis
- Iterative prototyping and evaluation
- Machine learning and predictive modeling
Research Areas
Extended Reality (XR/VR)
Investigating immersive technologies and their applications in enhancing human experiences and interactions in virtual and augmented environments.
Haptic Feedback
Exploring tactile and vibrotactile feedback mechanisms to create more immersive and intuitive interactions in virtual environments.
Gesture Tracking
Developing predictive algorithms for hand gesture recognition and tracking to reduce latency and improve interaction naturalness in XR systems.
Usability Engineering
Applying user-centered design principles and empirical evaluation methods to assess and improve the usability of interactive systems.
Research Interests
Current & Future Work
I am currently investigating how proactive vibrotactile cues can manipulate perceived haptic sensations in virtual reality, exploring the temporal boundaries of multisensory integration. My work aims to establish design principles for creating more responsive and natural XR interactions.
Future research directions include exploring the role of multimodal feedback in complex XR tasks, investigating individual differences in perception and prediction, and developing adaptive systems that can personalize interactions based on user behavior and preferences.