Chen (Cherise) Chen is a post-doc researcher in the Oxford BioMedIA group, University of Oxford, and an honorary research fellow at Imperial College London. Previously, she was a post-doc researcher in Computing Department at Imperial College London (ICL) and a part-time research scientist at HeartFlow after she obtained her PhD. degree in 2022 from the Department of Computing, Imperial College London, supervised by Professor Daniel Rueckert. Her main research interest lies in the interdisciplinary area of artificial intelligence (AI) and healthcare with expertise in medical image analysis, e.g., medical image segmentation, focusing on building and verifying robust, data-efficient machine learning algorithms to scale up AI-powered medical image analysis algorithms in real-world applications.
Awards and Honours
- 2022: IEEE TMI Gold-level Distinguished Reviewer (2020-2022)
- 2022: Winner of the Fetal Tissue Annotation and Segmentation Challenge (FeTA) Challenge
- 2019: Winner of the Multi-sequence Cardiac MR Segmentation Challenge 2019
- External Position:
2023-2026: Honorary research fellow at Imperial College London
- Medical image analysis (image synthesis, image segmentation and registration, shape modeling and analysis)
- Adversarial Machine Learning for Model Robustness
- Model generalization and Adaptation (unsupervised domain adaptation, test time adaptation)
- Data-efficient learning (single domain generalization, self-supervised learning, semi-supervised learning)
- Multi-modality and Multi-task learning
Artificial intelligence for cardiovascular research: AI for deep phenotyping and target discovery for precise medicine.