Yaxiong Xie
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Previous Organizations / Institutes
The organizations / institutes from the scholar's other articles in the past ten years
Research Subjects
Yaxiong Xie has a total of 86 co-authors. Here are the top co-authors by number of shared publications:
- Xiaojiang Chen
Northwest University
8 shared publications - Daqing Zhang
Peking University
5 shared publications - Duo Zhang
Peking University, Beijing, China
5 shared publications - Xusheng Zhang
Peking University, Beijing, China
5 shared publications - Kyle Jamieson
Princeton University, Princeton, NJ, USA
4 shared publications - Dan Xu
Northwest University, Xi'an, China
3 shared publications
Latest Publications
- Open Access
- 26 October 2026
- Published by Association for Computing Machinery (ACM)
- p. 265-281
OrbWeaver: A Geometric Optics-Based RIS for Omnidirectional 3D Beam Steering
- 26 October 2026
- Published by Association for Computing Machinery (ACM)
- p. 265-281
Open AccessOrbWeaver: A Geometric Optics-Based RIS for Omnidirectional 3D Beam Steering
- Open Access
- 26 October 2026
- Published by Association for Computing Machinery (ACM)
- p. 160-177
Attacking mmWave Imaging Using Metasurfaces Based on Intensity and Time-of-Flight Manipulation
- 26 October 2026
- Published by Association for Computing Machinery (ACM)
- p. 160-177
Open AccessAttacking mmWave Imaging Using Metasurfaces Based on Intensity and Time-of-Flight Manipulation
- Open Access
- 26 October 2026
- Published by Association for Computing Machinery (ACM)
- p. 12-15
Towards Deployment-Aware Evaluation of COTS mmWave Radar for Privacy-Aware Surveillance
- 26 October 2026
- Published by Association for Computing Machinery (ACM)
- p. 12-15
Open AccessTowards Deployment-Aware Evaluation of COTS mmWave Radar for Privacy-Aware Surveillance
- Open Access
- 11 August 2026
- Published by Association for Computing Machinery (ACM)
- p. 284-300
RANPilot: Making AI Functionalities Robust to Dynamic O-RAN Reconfigurations
- 11 August 2026
- Published by Association for Computing Machinery (ACM)
- p. 284-300
Open AccessRANPilot: Making AI Functionalities Robust to Dynamic O-RAN Reconfigurations
- Open Access
- 11 August 2026
- Published by Association for Computing Machinery (ACM)
- p. 301-316
Synchronizing with the Scheduler: Dual-Loop Congestion Control for 5G Uplink on Commodity Devices
- 11 August 2026
- Published by Association for Computing Machinery (ACM)
- p. 301-316
Open AccessSynchronizing with the Scheduler: Dual-Loop Congestion Control for 5G Uplink on Commodity Devices
- Open Access
- 10 May 2026
- Published by Association for Computing Machinery (ACM)
- p. 1144-1157
RAN-Aware Delay Compensation for Delay-Sensitive Protocols in Cellular Networks
- 10 May 2026
- Published by Association for Computing Machinery (ACM)
- p. 1144-1157
Open AccessRAN-Aware Delay Compensation for Delay-Sensitive Protocols in Cellular Networks
- 29 April 2026
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Networking
- Vol. 34, 5053-5065
SpeedPest: Accurate Multi-Pesticide Detection With NFC-Based Rapid Response Tag
Pesticide overuse poses significant risks to human health and environmental integrity. Addressing the limitations of existing approaches, which struggle with the diversity of pesticide compounds, portability issues, and detection efficiency, this paper introduces SpeedPest. A wireless and battery-free electrochemical tag that integrates the advantages of NFC technology with electrochemical biosensors for portable, high-accuracy, and fast multi-pesticide detection. The basic idea of SpeedPest is comparing the distinct electrochemical responses between a pair of biological receptors and different pesticides to construct a unique set of feature fingerprints to make multi-pesticide sensing feasible. To incorporate this idea within small NFC tags, we reengineer the electrochemical sensor, spanning the antenna to the voltage regulator. Additionally, to improve the system’s sensitivity and detection efficiency, we design electrode superimposed noise removal method and fast pesticide detection algorithm. Experiments with six different pesticides demonstrate that SpeedPest achieves an average accuracy of 97.78% in overall detection and 100% accuracy in concentration detection across all tested samples. Its sensitivity and rapid response remarkably outperform current state-of-the-art methods.
- 29 April 2026
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Networking
- Vol. 34, 5053-5065
SpeedPest: Accurate Multi-Pesticide Detection With NFC-Based Rapid Response Tag
Pesticide overuse poses significant risks to human health and environmental integrity. Addressing the limitations of existing approaches, which struggle with the diversity of pesticide compounds, portability issues, and detection efficiency, this paper introduces SpeedPest. A wireless and battery-free electrochemical tag that integrates the advantages of NFC technology with electrochemical biosensors for portable, high-accuracy, and fast multi-pesticide detection. The basic idea of SpeedPest is comparing the distinct electrochemical responses between a pair of biological receptors and different pesticides to construct a unique set of feature fingerprints to make multi-pesticide sensing feasible. To incorporate this idea within small NFC tags, we reengineer the electrochemical sensor, spanning the antenna to the voltage regulator. Additionally, to improve the system’s sensitivity and detection efficiency, we design electrode superimposed noise removal method and fast pesticide detection algorithm. Experiments with six different pesticides demonstrate that SpeedPest achieves an average accuracy of 97.78% in overall detection and 100% accuracy in concentration detection across all tested samples. Its sensitivity and rapid response remarkably outperform current state-of-the-art methods.
- Open Access
- 25 February 2026
- Published by Association for Computing Machinery (ACM)
- p. 25-30
EyeDAR: A Low-Power mmWave Tag that Senses and Communicates 3D Point Clouds to Enhance Radar Perception
- 25 February 2026
- Published by Association for Computing Machinery (ACM)
- p. 25-30
Open AccessEyeDAR: A Low-Power mmWave Tag that Senses and Communicates 3D Point Clouds to Enhance Radar Perception
- Open Access
- 3 November 2025
- Published by Association for Computing Machinery (ACM)
- p. 375-390
From Signal-based to Impedance-based Sensing: A paradigm Shift for Plug-and-Play, Mobile, and Sensitive Battery-free Sensing
- 3 November 2025
- Published by Association for Computing Machinery (ACM)
- p. 375-390
Open AccessFrom Signal-based to Impedance-based Sensing: A paradigm Shift for Plug-and-Play, Mobile, and Sensitive Battery-free Sensing
- Open Access
- 27 August 2025
- Published by Association for Computing Machinery (ACM)
- p. 994-1008
Enabling Over-the-Air AI for Edge Computing via Metasurface-Driven Physical Neural Networks
- 27 August 2025
- Published by Association for Computing Machinery (ACM)
- p. 994-1008
Open AccessEnabling Over-the-Air AI for Edge Computing via Metasurface-Driven Physical Neural Networks