MetaTap: Resonance-Splitting-Based Multi-Dip Encoding for High-Resolution Water Contaminant Sensing
Conference: UbiComp 2026
I build physics-informed sensing systems for environmental intelligence using emerging modalities such as RF, metasurfaces, UWB radar, mmWave sensing, and multimodal learning. My work focuses on translating complex environmental signals into accessible and actionable information for real-world applications such as water quality monitoring, soil sensing, and intelligent agriculture.
Conference: UbiComp 2026
Conference: UbiComp 2026
Conference: MobiSys 2024
I develop robust and efficient machine learning systems for real-world deployment. My research focuses on learning under missing, delayed, or heterogeneous data, with an emphasis on cross-modality inference, representation learning, and adaptive intelligence in resource-constrained environments.
Conference: UbiComp 2023
I collaborate on intelligent systems for secure and trustworthy human-computer interaction. Our work explores sensing-driven authentication, behavioral understanding, and privacy-aware perception, with applications in biometric security, gesture understanding, and robust user-facing intelligence.
Journal: IEEE TMC 2026