Jindong Gu

Postdoctoral Researcher, University of Oxford

I am a Postdoc at University of Oxford, working with Prof. Philip H. S. Torr. Prior to that, I received my Ph.D. Degree from University of Munich in 2022, advised by Prof. Volker Tresp.
My research interests include Computer Vision and Machine Learning. Especially, I am interested in building reliable AI by making AI models explainable, robust, and efficient.


[Hiring!] I am looking for visiting students/interns for our group in the area of robustness.
Please drop me an email (jindong DOT gu AT outlook DOT com) if interested.

News

Nov. 2022 I join Torr Vision Group as Postdoctoral Researcher at University of Oxford.
Aug. 2022 I join Google Responsible AI Team as a Research Intern.
Jul. 2022 Four papers on Robustness of Vision Systems have been accepted to ECCV 2022.
Apr. 2021 I join Microsoft Research Asia as a Research Intern.
Mar. 2021 One paper has been accepted as oral to CVPR 2021.
Jan. 2021 One paper has been accepted to ICLR 2021.
Oct. 2020 I join Tencent AI Lab as a Research Intern.

Education

Sept. 2017 - Oct. 2022 Ph.D. Degree, Computer Science in University of Munich
Mar. 2022 - Aug. 2022 Visiting Ph.D. Student, Torr Vision Group in University of Oxford
Apr. 2016 - Jul. 2017 Master Degree, Computer Science in University of Munich
Sept. 2011 - Mar. 2016 Double Bachelor Degrees, University of Wuppertal and Wuhan University

Experience

Nov. 2022 - present Postdoctoral Researcher at University of Oxford, Oxford, UK
Aug. 2022 - Nov. 2022 Research Intern at Google Brain, New York, USA
Apr. 2021 - Feb. 2022 Research Intern at Microsoft Research Asia, Beijing, China
Aug. 2020 - Mar. 2021 Research Intern at Tencent AI Lab, Shenzhen, China
Sept. 2017 - Aug. 2020 Doctoral Researcher at Siemens Technology, Munich, Germany

Selected Publications

    • Are Vision Transformers robust to Patch-wise Perturbation? [PDF]
      Jindong Gu, Volker Tresp, Yao Qin
      European Conference on Computer Vision (ECCV) , 2022
    • SegPGD: An Effective and Efficient Adversarial Attack for Evaluating and Boosting Segmentation Robustness [PDF]
      Jindong Gu, Hengshuang Zhao, Volker Tresp, Phillip Torr
      European Conference on Computer Vision (ECCV) , 2022
    • Towards Efficient Adversarial Training on Vision Transformers [PDF]
      Boxi Wu*, Jindong Gu*, Zhifeng Li, Deng Cai, Xiaofei He, Wei Liu
      European Conference on Computer Vision (ECCV) , 2022
    • Watermark Vaccine: Adversarial Attacks to Prevent Watermark Removal [PDF]
      Liu Xinwei, Jian Liu, Yang Bai, Jindong Gu, Tao Chen, Xiaojun Jia, Xiaochun Cao
      European Conference on Computer Vision (ECCV) , 2022
    • Capsule Network is Not More Robust than Convolutional Network [PDF]
      Jindong Gu, Volker Tresp, Han Hu
      IEEE Conference on Computer Vision and Pattern Recognition (CVPR) , 2021
    • Effective and Efficient Vote Attack on Capsule Networks [PDF][CODE]
      Jindong Gu, Baoyuan Wu, Volker Tresp
      International Conference on Learning Representations (ICLR) , 2021
    • Interpretable Graph Capsule Networks for Object Recognition [PDF] [CODE]
      Jindong Gu
      AAAI Conference on Artificial Intelligence (AAAI) , 2021
    • Simple Distillation Baselines for Improving Small Self-supervised Models [PDF] [CODE]
      Jindong Gu, Wei Liu, Yonglong Tian
      Workshop in ICCV , 2021
    • Improving the Robustness of Capsule Networks to Image Affine Transformations [PDF]
      Jindong Gu, Volker Tresp
      IEEE Conference on Computer Vision and Pattern Recognition (CVPR) , 2020
    • Search for Better Students to Learn Distilled Knowledge [PDF]
      Jindong Gu, Volker Tresp
      European Conference on Artificial Intelligence (ECAI) , 2020
    • Saliency Methods for Explaining Adversarial Attacks [PDF]
      Jindong Gu, Volker Tresp
      Human-Centric Machine Learning Workshop in NeurIPS , 2019
    • Understanding Individual Decisions of CNNs via Contrastive Backpropagation [PDF] [CODE]
      Jindong Gu, Volker Tresp
      Asian Conference on Computer Vision (ACCV), 2018

Professional Activities

  • Conference Reviewer:
    - International Conference on Machine Learning (ICML) 2022
    - International Conference on Learning Representations (ICLR) 2022-2023
    - Advances in Neural Information Processing Systems (NeurIPS) 2021-2022
    - European Conference on Computer Vision (ECCV) 2022
    - IEEE International Conference on Computer Vision (ICCV) 2021
    - IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2021-2023
  • Journal Reviewer:
    - Elsevier - Neurocomputing
    - Elsevier - Pattern Recognition
    - Transactions of Machine Learning Research (TMLR)
    - IEEE Transactions on Neural Networks and Learning Systems (TNNLS)
    - IEEE Transactions on Circuits and Systems for Video Technology (TCSVT)
    - IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)

Patents and Inventions

  • Verification of classification decisions in Convolutional Neural Networks,
    European Patent Office, EP3654248
  • A method for computer-implemented analysis of a classification model,
    Patent Family: EP3726433, CN111832572, US2020334489
  • Siemens Inventions: 8 AI Inventions in Siemens Technology, Germany

Honours and Awards

  • Google Stipend
  • Chinese Government Award for Outstanding Self-financed Students Abroad
  • CVPR22 Doctoral Consortium Award
  • University of Oxford Visiting Grant