HUANG Ling

HUANG Ling is a Research Fellow at the Saw Swee Hock School of Public Health, National University of Singapore (NUS). Her research focuses on trusted and explainable AI, uncertainty modeling, and medical data analysis using deep learning and evidence theory. She holds a Ph.D. from Université de Technologie de Compiègne (France), an M.Sc. from Zhejiang University of Technology (China), and a Bachelor’s from Anhui University of Technology (China).

Her work emphasizes applying belief functions and evidential reasoning to medical image segmentation, particularly in contexts with uncertain or imprecise data. Key contributions include semi-supervised learning for brain tumor segmentation, multimodal fusion for medical imaging, and applications in oncology and critical care.

Publications highlight advancements in uncertainty quantification, multimodal fusion, and AI-driven healthcare solutions. Her research bridges theoretical foundations (e.g., Gaussian random fuzzy numbers) with practical healthcare challenges, such as mortality prediction and disease classification.

Education:

• Ph.D., Université de Technologie de Compiègne, France (2019–2023)
• M.Sc., Zhejiang University of Technology, China (2016–2019)
• Bachelor’s, Anhui University of Technology, China (2012–2016)

Her research trends emphasize integrating evidence theory with deep learning to address uncertainty in healthcare data. Collaborations include projects on PET/CT imaging, EHR analysis, and adversarial learning for medical image retrieval.