Dongdong Chen 陈东东

  Research Associate

  The University of Edinburgh, Edinburgh, UK

  d.chen@ed.ac.uk

 

SCU UoE

I am a Postdoctoral Research Associate on Computational Sensing and Machine Learning working with Prof. Mike Davies in the University of Edinburgh. Before that, I received my PhD in computer science from Sichuan University in 2017, under the supervision of Prof. Jiancheng Lv. My research interests are machine learning, deep learning, computational imaging, and inverse problems. 

News

  • [14/09/2022] 1 paper (Multi-Operator Imaging) is accepted to NeurIPS'22.
  • [01/09/2022] 1 paper (Imaging with Equivariant Deep Learning) is accepted to IEEE Signal Processing Magazine (SPM).
  • [28/03/2022] 1 paper (Robust Equivariant Imaging) is accepted to CVPR'22 (oral).
  • [07/01/2022] 1 paper is accepted to ISBI'22.
  • [08/12/2021] Giving an invited talk in University of Cambridge.
  • [14/10/2021] Our ICCV paper (Equivariant Imaging) is featured in ICCV Daily.
  • [29/07/2021] 1 paper is accepted to IEEE TMI.
  • [22/07/2021] 1 paper (Equivariant Imaging) is accepted to ICCV'21 (oral).
  • [03/07/2020] 1 paper is accepted to ECCV'20.
  • [23/06/2020] 1 paper is accepted to MICCAI'20.
  • [20/05/2020] 1 paper is accepted to IEEE TSYS.
  • [03/11/2019] 1 paper is accepted to IEEE TNNLS.
  • [29/06/2019] 1 paper is accepted to MICCAI'19.
  • [15/05/2019] 2 papers are accepted to SPARS'19.
  • [06/05/2019] 2 papers are accepted to MIDL'19.
  • [01/02/2019] 2 papers are accepted to ICASSP'19.
  • [22/08/2018] 2 papers are accepted to iTWIST'18.
  • [08/01/2018] I joined the University of Edinburgh and IDCOM as a Postdoctoral Research Associate.

  • Selected Publications

       

    Imaging with Equivariant Deep Learning
    Dongdong Chen, Mike E. Davies, Matthias J. Ehrhardt, Carola-Bibiane Schönlieb, Ferdia Sherry and Julián Tachella
    IEEE Signal Processing Magazine (SPM), 2022
    arXiv

       

    Sampling Theorems for Unsupervised Learning in Linear Inverse Problems
    Julián Tachella,Dongdong Chen and Mike E. Davies
    tech report, 2022
    arXiv

       

    Unsupervised Learning From Incomplete Measurements for Inverse Problems
    Julián Tachella,Dongdong Chen and Mike E. Davies
    Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS), 2022
    arXiv code

       

    Robust Equivariant Imaging: a fully unsupervised framework for learning to image from noisy and partial measurements
    Dongdong Chen*, Julián Tachella* and Mike E. Davies
    IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Oral, 2022
    arXiv IEEE/CVF code talk

       

    Equivariant Imaging: Learning Beyond the Range Space
    Dongdong Chen*, Julián Tachella and Mike E. Davies
    International Conference on Computer Vision (ICCV), Oral, 2021
    arXiv IEEE/CVF post code talk

       

    Dual Convolutional Neural Networks for Breast Mass Segmentation and Diagnosis in Mammography
    Heyi Li, Dongdong Chen, Bill Nailon, Mike Davies and Dave Laurenson
    IEEE Transactions on Medical Imaging (IEEE TMI), 2021
    pdf (IEEE Xplore)

       

    Deep Decomposition Learning for Inverse Imaging Problems
    Dongdong Chen and Mike E. Davies
    European Conference on Computer Vision (ECCV), 2020
    arXiv   code

       

    Compressive MRF reconstruction with neural proximal gradient iterations
    Dongdong Chen, Mike E Davies, and Mohammad Golbabaee
    International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2020
    arXiv   ISBI'22 extension   code

       

    COIN: Contrastive Identifier Network for Breast Mass Diagnosis in Mammography
    Heyi Li*, Dongdong Chen*, Bill Nailon, Mike Davies and Dave Laurenson
    tech report, 2020
    arXiv

       

    An Improved Dual-Channel Network to Eliminate Catastrophic Forgetting
    Dongbo Liu, Zhenan He, Dongdong Chen and Jian Cheng Lv
    IEEE Transactions on Systems, Man, and Cybernetics: Systems (IEEE TSYS), accepted in May. 2020
    IEEE Xplore

       

    A Network Framework For Small-Sample Learning
    Dongbo Liu, Zhenan He, Dongdong Chen and Jian Cheng Lv
    IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS), accepted in Nov. 2019
    IEEE Xplore

       

    Signed Laplacian Deep Learning with Adversarial Augmentation for Improved Mammography Diagnosis
    Heyi Li*, Dongdong Chen*, Bill Nailon, Mike Davies and Dave Laurenson
    International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2019
    pdf

       

    Deep Fully Convolutional Network for MR Fingerprinting
    Dongdong Chen, Mohammad Golbabaee, Pedro A Gómez, Marion I Menzel and Mike E Davies
    International Conference on Medical Imaging with Deep Learning (MIDL), 2019
    pdf

       

    Spatio-temporal regularization for deep MR Fingerprinting
    Mohammad Golbabaee, Dongdong Chen, Mike E. Davies, Marion I. Menzel and Pedro A. Gomez
    International Conference on Medical Imaging with Deep Learning (MIDL), 2019
    pdf

       

    A fully convolutional network for MR Fingerprinting
    Dongdong Chen, Mohammad Golbabaee, Pedro A. Gomez, Marion I. Menzel and Mike E. Daveis
    The Signal Processing with Adaptive Sparse Structured Representations Workshop (SPARS), 2019
    arXiv

       

    Deep learning for Magnetic Resonance Fingerprinting
    Mohammad Golbabaee, Dongdong Chen, Pedro A. Gomez, Marion I. Menzel and Mike E. Davies
    The Signal Processing with Adaptive Sparse Structured Representations Workshop (SPARS), 2019
    arXiv

       

    A Deep Dual-Path Network For Improved Mammogram Image Processing
    Heyi Li, Dongdong Chen, Bill Nailon, Mike Davies and Dave Laurenson
    International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2019
    IEEE Xplore   code

       

    Geometriy of Deep Learning for Magnetic Resonance Fingerprinting
    Mohammad Golbabaee, Dongdong Chen, Pedro A. Gomez, Marion I. Menzel and Mike E. Davies
    International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Oral, 2019
    arXiv

       

    Learning Discriminative Representation with Signed Laplacian Restricted Boltzmann Machine
    Dongdong Chen, Jiancheng Lv and Mike E. Daveis
    The international Traveling Workshop on Interactions between low-complexity data models and Sensing Techniques (iTWIST), 2018
    arXiv

       

    A deep learning approach for Magnetic Resonance Fingerprinting
    Mohammad Golbabaee, Dongdong Chen, Pedro A. Gomez, Marion I. Menzel and Mike E. Davies
    The international Traveling Workshop on Interactions between low-complexity data models and Sensing Techniques (iTWIST), 2018
    arXiv

       

    Improved Breast Mass Segmentation in Mammograms with Conditional Residual U-net
    Heyi Li, Dongdong Chen, Bill Nailon, Mike Davies and Dave Laurenson
    MICCAI Workshop (BIA), 2018. Best Student Paper Nomination
    arXiv

       

    Graph regularized Restricted Boltzmann Machines
    Dongdong Chen, Jian Cheng Lv and Zhang Yi
    IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS), accepted in 2017. SCF Best Student Paper Award
    IEEE Xplore code

       

    Angle-based Embedding Quality Assessment Method for Manifold Learning
    Dongdong Chen, Jiancheng Lv, Jing Yin, Haixian Zhang and Xiaojie Li
    Neural Computing & Applications (NCAA), accepted in 2017
    pdf

       

    Unsupervised Multi-Manifold Clustering by Learning Deep Representation
    Dongdong Chen, Jiancheng Lv and Zhang Yi
    AAAI Workshop, 2017
    pdf

       

    Angle-based Outlier Detection Algorithm with More Stable Relationships
    Xiaojie Li, Jian Cheng Lv and Dongdong Chen
    The Asia Pacific Symposium on Intelligent and Evolutionary Systems (IES), 2014. Best Student Paper Award
    pdf

       

    A Local Non-negative Pursuit Method for Intrinsic Manifold Structure Preservation
    Dongdong Chen, Jian Cheng Lv and Zhang Yi
    AAAI Conference on Artificial Intelligence (AAAI), 2014
    pdf code

      

    Awards and Honors


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