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Julian Wyatt

Personal photo - Julian Wyatt

Julian Wyatt

Doctoral Student

E: julian.wyatt@cs.ox.ac.uk

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Interests

My research interests are:

  • Self-supervised methods
  • Anomaly detection
  • Generative Models
  • Multimodal deep learning

Biography

Julian is a DPhil student in Computer Science, working in the OxMedIS research group. He previously completed an integrated Masters in Computer Science at Durham, which led to his persuit of a DPhil.

His research focuses on self-supervised machine learning methods and applications within the medical domain. Mainly applied to medical landmark detection: a method used by clinicians to produce explainable diagnosis.

Julian's first year culminated in winning the Cephalometric Landmark Detection Challenge @ MICCAI 2024. His approach utilised an RCNN and novel augmentation techniques to align cephalograms from diverse domains.

Prior to Julian's Oxford research he worked with Dr Chris Willcocks and published work on unsupervised anomaly detection with diffusion models at CVPR workshops 2022 (AnoDDPM)

 

Selected Publications

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Supervisor