My research asks how immersive systems can infer user state responsibly, anticipate risk, personalize support, and remain practical under real sensing and deployment constraints.
I develop models for continuous cognitive load, engagement, user performance, and uncertainty-aware prediction across changing XR contexts. A recurring goal is to move beyond static labels toward temporally meaningful, user-sensitive estimates.
I study cybersickness forecasting, probabilistic verification, personalized susceptibility modeling, and hazard-aware MR systems. This includes both predictive modeling from multimodal signals and system-level interventions that help users before risk becomes critical.
XR sensors capture behavioral signals that can expose sensitive attributes. My work explores targeted feature obfuscation, progressive adversarial privacy, and privacy–utility tradeoffs that reduce demographic leakage while preserving task-relevant information.
As a Graduate Research Assistant in HiX Lab, I contribute to DARPA-funded research on intrinsic cognitive security, including engagement, cognitive state modeling, immersive-system safety, and privacy. Award: HR00112420366.