Augmented Reality
INSTAR's augmented reality research explores how spatial computing and human-computer interaction can extend scientific perception and operational capability. We investigate XR systems that make invisible phenomena tangible — overlaying computed data onto physical environments for research, specialized training, and collaborative scientific work across distances.
AR Display & Optics Research
INSTAR investigates optical see-through and video see-through display architectures, examining tradeoffs in field of view, weight, latency, and brightness that govern professional usability. Research interest spans waveguide design, holographic optical elements, and display-stack integration — the physical bottlenecks that determine whether AR headsets can support extended fieldwork, clinical settings, or precision laboratory environments.
Spatial Computing & Scene Understanding
Effective AR depends on precise, persistent understanding of physical space. INSTAR's spatial computing research examines real-time 3D mapping, visual-inertial localization, LiDAR sensor fusion, and semantic scene representation — the stack required to reliably anchor digital content in dynamic, uncontrolled environments. We explore how these capabilities enable shared, multi-user AR sessions for distributed research teams and remote scientific collaboration.
Scientific Visualization & Human Interaction
INSTAR studies how AR interfaces can transform the way researchers engage with complex scientific data — molecular structures, neuroimaging volumes, geospatial terrain models, and high-dimensional simulation outputs. We investigate natural interaction modalities including gesture, gaze, and voice that match the exploratory workflows of domain scientists. The goal is human-computer interaction design that reduces cognitive load and accelerates insight without imposing engineering overhead on the researcher.
Collaborative & Training Applications
AR's public benefit case is strongest in applications where presence and co-location matter but are impractical — specialized training, remote expert guidance, and distributed team experimentation. INSTAR examines AR interaction designs for these contexts: sharing annotated physical specimens, reviewing 3D models across geographically separated sites, and conducting supervised laboratory procedures with remote instructors. This work connects directly to INSTAR's Fellowship program, where early-career researchers from physics, cognitive science, and computer science investigate the boundaries of XR-enabled collaboration. Interested PhD graduates are invited to apply at /fellowship/.
OUR PARTNERS
