Chen Chen

Chen Chen

Lecturer (Assistant Professor) in Computer Vision

Chen (Cherise) Chen

Be water. 居善地，心善渊，与善仁，言善信，政善治，事善能，动善时。

Bio

Dr Chen (Cherise) Chen is a Lecturer in Computer Vision, at the Department of Computer Science, University of Sheffield, and a core member of Insigeno Institute, Center for Machine Intelligence, and Shef.AI community. She is one of six academics leading the Computer Vision research group at Sheffield. She also currently holds honorary research fellow positions at both the University of Oxford and Imperial College London. Previously, she was a post-doc at Oxford BioMedIA group, University of Oxford, and the Computing Department at Imperial College London (ICL). She was also a research scientist at HeartFlow. In 2022, she obtained her Ph.D. from the Department of Computing at Imperial College London, working closely with Prof. Daniel Rueckert and Dr. Wenjia Bai. Her doctoral thesis, entitled “Improving the domain generalization and robustness of neural networks for medical imaging,” was featured in ComputerVisionNews magazine in 2022.

Opening

We have opening positions for PhD students on robust and adaptive AI for healthcare, see Vacancies for details.

News

24/04/2024
Invited to give a talk at BMVA symposium on "Trustworthy Multimodal Learning with Foundation Models: Bridging the Gap between AI Research and Real World Applications", British Computer Society (BCS), London. [More]
05/04/2024
Invited as a lead panelist on the MICCAI student webinar: A Panel Discussion on the Trips & Tips of MICCAI Review, Rebuttal, Challenge, and Workshop! [More]
03/2024
Happy to announce that a Joint Workshop on Advancing Data Solutions in Medical Imaging AI (ADSMI)x The 4th Workshop on Data Augmentation, Labeling, and Imperfections (DALI) will be held in MICCAI 2024.
01/02/2024
I am invited to be the area chair (AC) for MICCAI 2024!
12/01/2024
One article was accepted by IEEE TMI on synthetic data generation for retinal vessel segmentation. Congrats to Linus Kreitner!
06/11/2023
Joined the Department of Computer Science at Uni of Sheffield as a Lecturer/Assistant Professor in Computer Vision
12/10/2023
Received IEEE TMI Gold-level Distinguished Reviewer Award (2022-2023)!
19/07/2023
Received one of the top 12 Outstanding Reviewer awards in MICCAI 2023!
19/07/2023
One paper working on efficient, effective vision language pre-training (M-Flag) got accepted to MICCAI 2023. Congrats to Che LIU!
17/05/2023
Invited to give a talk at NCT Data Science Seminar 2023 at the German Cancer Research Center (DKFZ)

Research Interest

My main research interest lies in the interdisciplinary area of artificial intelligence (AI) and healthcare with a particular focus on medical image analysis, e.g., medical image segmentation, focusing on building and verifying robust, data-efficient, reliable machine learning algorithms to scale up AI-powered medical image analysis in real-world applications. Below are some topics I have explored:

  • Adversarial data augmentation
  • Robust machine learning
  • Data-efficient learning: self-supervised learning, few-shot learning, semi-supervised learning
  • Multi-task and multi-modal learning
  • Adaptive machine learning, including unsupervised domain adaptation at training/test time
  • Algorithms with fairness, privacy, robustness, and interpretability in mind, including uncertainty-aware training, test time model calibration

I am extremely interested in their applications including:

  • cardiac image analysis (segmentation, registration, and shape remodeling) with quality control (e.g. topology preserving, uncertainty measurement), follow-up motion/shape analysis, survival prediction, treatment planning
  • prostate image analysis together with pathological image analysis, risk prediction, treatment planning
  • brain image segmentation and surface reconstruction for clinical applications.

Awards and honours

  • 2023: IEEE TMI Gold-level Distinguished Reviewer (2022-2023)
  • 2023: MICCAI 2023 Outstanding Reviewer (top 12)
  • 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
  • 2012&2013: China National Scholarships (twice) (top 0.2%): The highest level of national scholarships in China.

Contact

  • Email: chen (dot) chen2 (at) sheffield (dot) ac (dot) uk
  • Address: Regent court, Department of Computer Science, University of Sheffield, Sheffield, UK. S1 4DP