Differentiable Radio Frequency Digital Twin
ACM MobiCom 2026 · Demo Track · forthcoming
Simulation · sensing · machine learning
Wenxuan Guo
Master’s · UC San Diego
I’m interested in physically based simulation, synthetic data generation, and machine learning for real-world sensing.
Physics-based simulationSynthetic dataReal-world sensing
Projects
Selected Projects
Radar Data Synthesis
Physics-based simulation and controllable motion generation for labeled radar data across subjects, activities, and environments.
WiTwin Studio
An interactive 3D workspace for scene authoring, motion matching, animation timelines, and simulation preparation.
Research Intelligence Platform
Evidence-backed faculty profiles, monthly research digests, and collaboration discovery for more than 20 faculty members.
Research output
Publications & Presentations
Conference
Generative Radar Data Synthesis for Human–Animal Disambiguation
Amazon Hardware Organization Academic Innovation Partnership Poster Event · Oct 2026
Generative Radar Data Synthesis for In-Home Wireless Sensing
CWC Annual Research Review · UC San Diego · Oct 2026
Improving Proof Learning with Proof Blocks
CSE Undergraduate Research Symposium · University of Michigan · Apr 2025
Experience
Selected Experience
Jan 2026 — Present
Graduate Student Research Assistant
UC San Diego · ECE
Develop physics-based radar data synthesis and research software with Prof. Xinyu Zhang.
Jun 2026 — Present
Student Assistant
UC San Diego · Center for Wireless Communications
Build research information tools and support CWC’s web presence, communications, and community activities.
Contact