Dongdong Chen 陈东东

Machine Learning | Imaging | Inverse Problems

Assistant Professor
Heriot-Watt University, Edinburgh, UK

I am an Assistant Professor of Mathematical and Computer Sciences at Heriot-Watt University in Edinburgh. My research lies at the intersection of machine learning and image processing. My current focus is on inverse problems in computational imaging and computer vision.

I held a postdoctoral researcher position at the University of Edinburgh from 2018 to 2022. I then held an associate researcher position at Sichuan University until 2023, where I previously received my PhD in 2017.

Openings: If you are interested in doing a PhD, please email me with your CV/transcripts and a short research statement.


Aug 05, 2024 Invited talk at the IMSI Workshop on Computational Imaging, University of Chicago, USA.
May 02, 2024 Our paper on foundation models for image fusion (FILM) is accepted at ICML’24.
Feb 27, 2024 Our paper on equivariant image fusion (EMMA) is accepted at CVPR’24.
Jan 09, 2024 Invited talk at the IMS Young Mathematical Scientist Forum – Applied Math, National University of Singapore (NUS), Singapore.

selected publications

  1. ICCV OralFeatured
    Equivariant Imaging: Learning Beyond the Range Space
    Dongdong Chen, Julián Tachella , and Mike E Davies
    In IEEE/CVF International Conference on Computer Vision (ICCV) , 2021
    Oral Presentation (Featured in ICCV Daily)
  2. JMLR
    Sensing Theorems for Unsupervised Learning in Linear Inverse Problems
    Julián Tachella , Dongdong Chen, and Mike Davies
    Journal of Machine Learning Research (JMLR), 2023
    Imaging With Equivariant Deep Learning: From unrolled network design to fully unsupervised learning
    Dongdong Chen, Mike E Davies , J Matthias Ehrhardt , Carola-Bibiane Schönlieb , Ferdia Sherry , and Julián Tachella
    IEEE Signal Processing Magazine, 2023


Awards and Honors

  • MICCAI-BIA'18 Best Paper Nomination, 2018

  • Sichuan University Excellent Graduate, 2017

  • SCF Best Student Paper Award, 2017

  • IES Best Student Paper Award, 2014

  • National Scholarship, 2014

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