Interests
- Medical AI
- Interpretability and Confounder Problems in Machine Learning
- Geometric Deep Learning
- Imaging Genetics
- AI-based Epidemiological Studies
- 3D Facial Shape Analysis
Research lines
Projects
Biography
Xianjing is a postdoctoral researcher in medical image analysis at Erasmus MC department of Radiology & Nuclear Medicine, in collaboration with department of Internal Medicine. He primarily contributes to the EU horizon project PainFACT, studying assocaitions between the structrual brain MRI and pain perception. He completed his PhD thesis entitled 3D facial shape analysis at the same department of Erasmus MC, in collaboration with department of Oral & Maxillofacial Suegery. Earlier, he completed his Masters from Shenzhen University, and gained industrial experience as a R&D engineer at Shenzhen Wisonic Co., Ltd. and a researcher at Hong Kong Polytecnic University in collaboration with Esquel Group.
His research focuses on trustworthy and interpretable machine learning for healthcare applications, particularly addressing challenges related to bias, confounding factors, fairness, representation learning, and privacy-aware AI. He collaborates with domain experts in epidemiology, genetics, surgery, dermatology, and neuroscience, applying machine learning methods to association studies, imaging genetics, risk prediction, and multimodal clinical AI systems.