Yanling Hao

Yanling Hao is a Visiting Professor at the School of Electronic Engineering and Computer Science, Queen Mary University of London. Her research focuses on advanced sensing technologies, particularly in wireless human activity recognition and remote sensing applications. She specializes in developing lightweight, energy-efficient systems for real-time monitoring using WiFi signals and hyperspectral imaging techniques. Her work integrates machine learning, deep learning, and optimization algorithms to address challenges in privacy-aware human sensing, disaster damage assessment, and geospatial analysis.

Dr. Hao's research interests span multiple domains including wireless communication, computer vision, and signal processing. Her contributions include frameworks like LWiHS and LiteWiHAR, which leverage feature fusion and cross-modal autoencoders for enhanced accuracy in activity recognition. She also pioneers methods for hyperspectral image classification using Gabor filters and gravitational search algorithms, advancing applications in environmental monitoring and urban planning.

Her publications emphasize practical systems for real-world scenarios, such as rapid damage mapping after earthquakes and privacy-preserving human activity datasets. These innovations bridge theoretical research with tangible solutions for disaster management, smart environments, and sustainable urban development.

Though no specific awards or grants are listed, her prolific output in high-impact venues demonstrates her influence in interdisciplinary computational sensing research.