Ying Liang

Ying Liang is a multidisciplinary researcher with significant contributions across computer science, bioinformatics, and remote sensing. Their work spans AI-driven medical diagnostics, environmental monitoring, and computational biology, with recent focus on precision nutrition, skin lesion recognition, and urban heat island analysis.

• Research Interests: Machine learning for biomedical applications (e.g., skin cancer detection, pancreatic segmentation), remote sensing (landslide mapping, urban structure dynamics), and computational biology (RNA-protein interactions, microRNA regulation).
• Notable Article Trends: 2025 publications highlight self-supervised remote sensing classification, fractal reservoir modeling, and biomedical AI. 2024 works emphasize cross-domain gait recognition, panoptic segmentation, and health informatics via Wi-Fi sensing.
• Grants & Collaborations: Co-authored studies with institutions like Open University and Chinese universities, focusing on thermal cycling reliability, multi-omics data fusion, and wireless health monitoring.
• Labs & Teams: Collaborated on interdisciplinary projects involving neural network architectures, hybrid AI models for environmental and biomedical applications, and biomedical signal processing systems.