5G-Radiometer Coexistence Testbed for Spectrum Sharing Research
Hardware testbed for investigating spectrum coexistence between L-band radiometers and 5G wireless communication systems
Portfolio
RFI-Net: Deep Learning-Based RFI Detection in the Time-Frequency Domain
Deep learning-based RFI detection and mitigation for passive sensing using a dual-loss U-Net architecture
HRSpecNet: Deep Learning-Based High-Resolution Radar Micro-Doppler Signature Reconstruction
End-to-end deep learning framework for noise-robust, high-resolution micro-Doppler spectrogram generation and improved human activity recognition
CNN-Based RFI Detection for SMAP Radiometer
Convolutional neural network approach for robust radio-frequency interference detection in spaceborne L-band radiometer measurements
Deep Learning-Based Radiometer Calibration Framework
Deep learning-based calibration for passive microwave radiometers using physics-informed architectures
SDR-Based Dual-Polarized L-Band Microwave Radiometer for Small UAS Platforms
Compact, software-defined, dual-polarized L-band microwave radiometer for airborne remote sensing from small unmanned aerial systems
Precision Agriculture: Deep Learning-Driven Crop Mapping from Multi-Temporal Sentinel-2
Leveraging Sentinel-2 time-series data and deep learning to extract vegetation phenology metrics and deliver accurate crop mapping for precision agriculture