2 citations · 2 across the 5 of their papers we have counts for
7 papers
SenseAgent: An LLM Agent for Adaptive Cross-Domain IMU Sensing
Tianya Zhao, Chuan Liu, Xuyu Wang
Deep learning has improved inertial measurement unit (IMU) sensing for mobile and wearable applications. However, an IMU model trained in one domain often becomes unreliable when i…
CSI-Agent: LLM-Assisted Few-Shot Adaptation for Cross-Domain Wi-Fi CSI Sensing
Tianya Zhao, Chuan Liu, Xuyu Wang
Wi-Fi channel state information (CSI) has enabled device-free sensing applications such as human activity recognition. However, CSI sensing models remain brittle in cross-domain de…
A Geometric Algebra-Informed 3DGS Framework for Wireless Channel Prediction
Jingzhou Shen, Tianya Zhao, Xuyu Wang
In this paper, we introduce Geometric Algebra-Informed 3D Gaussian Splatting (GAI-GS), a framework for wireless modeling that couples 3D Gaussian splatting with a geometric algebra…
Generalizable and Interpretable RF Fingerprinting with Shapelet-Enhanced Large Language Models
Tianya Zhao, Junqing Zhang, Haowen Xu +3
Deep neural networks (DNNs) have achieved remarkable success in radio frequency (RF) fingerprinting for wireless device authentication. However, their practical deployment faces tw…
EMPalm: Exfiltrating Palm Biometric Data via Electromagnetic Side-Channel
Haowen Xu, Tianya Zhao, Xuyu Wang +4
Palm recognition has emerged as a dominant biometric authentication technology in critical infrastructure. These systems operate in either single-modal form, using palmprint or pal…
Protocol-agnostic and Data-free Backdoor Attacks on Pre-trained Models in RF Fingerprinting
Tianya Zhao, Ningning Wang, Junqing Zhang +1
While supervised deep neural networks (DNNs) have proven effective for device authentication via radio frequency (RF) fingerprinting, they are hindered by domain shift issues and t…
NeRF-APT: A New NeRF Framework for Wireless Channel Prediction
Jingzhou Shen, Tianya Zhao, Yanzhao Wu +1
Neural radiance fields (NeRFs) have recently attracted significant attention in the field of wireless channel prediction, primarily due to their capability for high-fidelity recons…