I am an Assistant Professor at the Department of Computer Science, City University of Hong Kong since January 2024. I received my Ph.D. and M.Phil degree from School of Computer Science, University of Sydney, supervised by Dr. Chang Xu. Before that, I received my BS degrees in Software Engineering and Information Technology from both Dalian University of Technology and University of Sydney. My research interests include trustworthy machine learning algorithms and their related applications in computer vision. Currently, my research focuses on: adversarial robustness, model calibration, efficient neural network, neural architecture search, generative model, and human motion analytics.

📯 Opening

I am looking for self-motivated MPhil/PhD students enrolled in the year of 2024. If you are interested in trustworthy machine learning research, computer vision, generative models, adversarial robustness, model calibration, or efficient neural networks, feel free to send me an email (dong_serj[AT]hotmail[dot]com), with your CV, transcript, and publication. Successful PhD applicants will enroll in 2024 with scholarship.

📝 Publications

ICLR 2024
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A Benchmark Study on Calibration

Linwei Tao, Younan Zhu, Haolan Guo, Minjing Dong, Chang Xu

International Conference on Learning Representations (ICLR), 2024

ICLR 2024
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Neural Architecture Retrieval

Xiaohuan Pei, Yanxi Li, Minjing Dong, Chang Xu

International Conference on Learning Representations (ICLR), 2024

AAAI 2024
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AMD: Autoregressive Motion Diffusion

Bo Han, Hao Peng, Minjing Dong, Chang Xu, Yi Ren, Yixuan Shen, Yuheng Li

AAAI Conference on Artificial Intelligence (AAAI), 2024

TMM 2023
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Stealthy Physical Masked Face Recognition Attack via Adversarial Style Optimization

Huihui Gong, Minjing Dong, Siqi Ma, Seyit Camtepe, Surya Nepal, Chang Xu

IEEE Transactions on Multimedia, 2023

NeurIPS 2023
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Adversarial Robustness through Random Weight Sampling

Yanxiang Ma, Minjing Dong, Chang Xu

Conference on Neural Information Processing Systems (NeurIPS), 2023

TIP 2023
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Improving Lightweight AdderNet via Distillation from ℓ2 to ℓ1-Norm

Minjing Dong, Xinghao Chen, Yunhe Wang, Chang Xu

IEEE Transactions on Image Processing, 2023

[Code]

AAAI 2023
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Neural architecture search for wide spectrum adversarial robustness

Zhi Cheng, Yanxi Li, Minjing Dong, Xiu Su, Shan You, Chang Xu

AAAI Conference on Artificial Intelligence (AAAI), 2023

AAAI 2023
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Boosting semi-supervised semantic segmentation with probabilistic representations

Haoyu Xie, Changqi Wang, Mingkai Zheng, Minjing Dong, Shan You, Chong Fu, Chang Xu

AAAI Conference on Artificial Intelligence (AAAI), 2023

[Code]

ICML 2023
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Dual Focal Loss for Calibration

Linwei Tao *, Minjing Dong *, Chang Xu

International Conference on Machine Learning (ICML), 2023

[Code]

CVPR 2023
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Adversarial Robustness via Random Projection Filters

Minjing Dong, Chang Xu

IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023

[Code]

IJCAI 2023
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Calibrating a Deep Neural Network with Its Predecessors

Linwei Tao, Minjing Dong, Daochang Liu, Changming Sun, Chang Xu

International Joint Conference on Artificial Intelligence (IJCAI), 2023

[Code]

NeurIPS 2022
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Random normalization aggregation for adversarial defense

Minjing Dong, Xinghao Chen, Yunhe Wang, Chang Xu

Conference on Neural Information Processing Systems (NeurIPS), 2022

[Project] [Code]

TPAMI 2022
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Neural architecture search via proxy validation

Yanxi Li, Minjing Dong, Yunhe Wang, Chang Xu

IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022

ICML 2022
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Spatial-channel token distillation for vision mlps

Yanxi Li, Xinghao Chen, Minjing Dong, Yehui Tang, Yunhe Wang, Chang Xu

International Conference on Machine Learning (ICML), 2022

Neurocomputing 2022
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Neural architecture tuning with policy adaptation

Yanxi Li, Minjing Dong, Yixing Xu, Yunhe Wang, Chang Xu

Neurocomputing, 2022

TNNLS 2022
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Skeleton-based human motion prediction with privileged supervision

Minjing Dong, Chang Xu

IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022

NeurIPS 2021
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An empirical study of adder neural networks for object detection

Xinghao Chen, Chang Xu, Minjing Dong, Chunjing Xu, Yunhe Wang

Conference on Neural Information Processing Systems (NeurIPS), 2021

NeurIPS 2021
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Handling long-tailed feature distribution in addernets

Minjing Dong, Yunhe Wang, Xinghao Chen, Chang Xu

Conference on Neural Information Processing Systems (NeurIPS), 2021

NeurIPS 2021
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Towards stable and robust addernets

Minjing Dong, Yunhe Wang, Xinghao Chen, Chang Xu

Conference on Neural Information Processing Systems (NeurIPS), 2021

ICML 2020
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Neural architecture search in a proxy validation loss landscape

Yanxi Li, Minjing Dong, Yunhe Wang, Chang Xu

International Conference on Machine Learning (ICML), 2020

TNNLS 2020
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Adversarial recurrent time series imputation

Shuo Yang, Minjing Dong, Yunhe Wang, Chang Xu

IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2020

IJCAI 2019
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Crafting Efficient Neural Graph of Large Entropy

Minjing Dong, Hanting Chen, Yunhe Wang, Chang Xu

International Joint Conference on Artificial Intelligence (IJCAI), 2019

IJCAI 2019
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On Retrospecting Human Dynamics with Attention

Minjing Dong, Chang Xu

International Joint Conference on Artificial Intelligence (IJCAI), 2019

[Code]

🏆 Awards

  • 2023, AAAI-23 Distinguished Paper Award (12/8777)
  • 2020, Faculty of Engineering Research Scholarship, University of Sydney

📖 Teaching

  • 2023, Guest Lecturer, HTIN5005: Applied Healthcare Data Science, University of Sydney
  • 2023, Guest Lecturer, COMP5329: Deep Learning, University of Sydney
  • 2019, Teaching Assistant, COMP5329: Deep Learning, University of Sydney

💗 Services

  • 2022-2023, Event Co-organizer of Coding Fest, University of Sydney
  • 2022, Event Co-organizer of DICTA 2022 Workshop
  • PC member of CVPR, ICML, AAAI, NeurIPS, ACMMM, ICLR, ICCV, ICDM, WCCI, WACV, KDD
  • Reviewer of Knowledge-based Systems, IEEE Transactions on Multimedia, Neurocomputing, Pattern Recognition, Transactions on Machine Learning Research

💬 Experience

  • 2020.07-2021.12, Research Intern in Noah’s Ark Lab
  • 2019.03-2019.12, Research Associate in University of Sydney

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Last Update: Nov 15, 2023