Rose Qingyang Hu
Virginia Polytechnic Institute and State University, VA·Engineering
Future wireless networks will need to do more than carry data. They will need to anticipate how signals behave as people and objects move.
- Fields
Engineering
Computer Science
- Topics
wireless communications
NextG wireless
channel state information
- Grants
- 4 known grants, through Jul 2030
What they work on
- Reconstruct how wireless signal energy varies with position and direction by combining sparse channel state information measurements with 3D environment layouts rebuilt from images, using radiance-field-inspired models and array signal processing.
- Validate data-efficient channel prediction across mmWave and sub-terahertz frequency bands under limited sensor coverage and partial line of sight, and release open-source data, code, and validation tools.
- Build a Radio Radiance Field that fuses radio measurements with on-headset perception to predict wireless channels for extended reality users moving through dynamic environments.
- Use these predictions to drive beamforming, scheduling, and handover through O-RAN xApps and rApps, linking XR head pose, gaze, and rendering priorities to network control, and test in learning and industrial scenarios.
- Develop methods for generating mobile Internet measurement data with explainable quality and usefulness, and for sharing and jointly analyzing that data while protecting privacy, evaluated with a new mobile traffic generator.
- Create an AI-assisted, remotely accessible self-driving nanofabrication platform that combines physics-informed models, machine learning, and human oversight, and validate it on meta-optics, plasmonic biosensors, flexible bioelectronics, and lithium niobate photonics.
More about the research
Sending a signal well depends on channel state information (CSI): knowing how radio waves bounce, fade, and travel between transmitter and receiver. This is especially hard at the very high frequencies planned for 6G. This research combines wireless communication with sensing and artificial intelligence (AI). Two projects use cameras and 3D maps of the surroundings to predict wireless signals, one for general channel modeling and one for extended reality headsets. A third project studies how to share mobile Internet measurement data without exposing users' privacy. A fourth builds an AI-assisted, remotely accessible lab for making nanoscale semiconductor devices.
Why it matters
More predictive wireless networks could make XR reliable enough for education, healthcare, manufacturing, and public-safety training. They could also make 6G high-frequency links practical indoors and in cities. Privacy-preserving data sharing could let network operators troubleshoot and plan mobile networks without exposing users. A remotely accessible, AI-assisted nanofabrication lab could cut the time and cost of developing electronic, photonic, and sensing devices, and open advanced fabrication tools to more researchers.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
NSF PCL-Test Bed: AI-enabled, Cloud-based Self-Driving Nanofabrication Node for Accelerating Semiconductor Research and Education
NSF · Aug 2026 – Jul 2030
Collaborative Research: VINES: Track 2: SCOPE-XR: Seeing the Channel: Optimizing Perception-aware Environments for XR
NSF · Sep 2026 – Aug 2029
Collaborative Research: CCSS: Rethinking Wireless Channel Through the Lens of Radiance Field
NSF · Sep 2025 – Aug 2028
Closest labs
Yasaman Ghasempour
Princeton University, NJ·Engineering·Early-career
Steer narrow terahertz beams electronically using a new multi-slit antenna, in which the beam's angle depends on the signal frequency and the slit geometry, to overcome the high signal loss at frequencies above 100 GHz.
Robert Heath
University of California-San Diego, CA·Engineering
Build MIMO input-output models of dynamic metasurface antennas (low-power panels of tunable elements) that capture waveguide loss, coupling between elements and reconfiguration effects, using existing circuit and antenna models.
Edmund Yeh
Northeastern University, MA·Engineering
Jointly optimize base station association, handover and uplink/downlink beamforming in 5G millimeter-wave networks to minimize wireless latency for mobile XR users.
The school
Virginia Polytechnic Institute and State University: 35 labs on PI Pages, $657M a year on research, 496 research doctorates a year.
More about Virginia Polytechnic Institute and State University
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