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 2025. 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 2025 with scholarship.
📝 Publications
Imitation Learning from Purified Demonstrations
Yunke Wang, Minjing Dong, Yukun Zhao, Bo Du, Chang Xu
International Conference on Machine Learning (ICML), 2024
Random Entangled Tokens for Adversarially Robust Vision Transformer
Huihui Gong, Minjing Dong, Siqi Ma, Seyit Camtepe, Surya Nepal, Chang Xu
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024
A Benchmark Study on Calibration
Linwei Tao, Younan Zhu, Haolan Guo, Minjing Dong, Chang Xu
International Conference on Learning Representations (ICLR), 2024
Xiaohuan Pei, Yanxi Li, Minjing Dong, Chang Xu
International Conference on Learning Representations (ICLR), 2024
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
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
Adversarial Robustness through Random Weight Sampling
Yanxiang Ma, Minjing Dong, Chang Xu
Conference on Neural Information Processing Systems (NeurIPS), 2023
Improving Lightweight AdderNet via Distillation from ℓ2 to ℓ1-Norm
Minjing Dong, Xinghao Chen, Yunhe Wang, Chang Xu
IEEE Transactions on Image Processing, 2023
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
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
Dual Focal Loss for Calibration
Linwei Tao *, Minjing Dong *, Chang Xu
International Conference on Machine Learning (ICML), 2023
Adversarial Robustness via Random Projection Filters
Minjing Dong, Chang Xu
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023
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
Random normalization aggregation for adversarial defense
Minjing Dong, Xinghao Chen, Yunhe Wang, Chang Xu
Conference on Neural Information Processing Systems (NeurIPS), 2022
Neural architecture search via proxy validation
Yanxi Li, Minjing Dong, Yunhe Wang, Chang Xu
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022
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
Neural architecture tuning with policy adaptation
Yanxi Li, Minjing Dong, Yixing Xu, Yunhe Wang, Chang Xu
Neurocomputing, 2022
Skeleton-based human motion prediction with privileged supervision
Minjing Dong, Chang Xu
IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022
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
Handling long-tailed feature distribution in addernets
Minjing Dong, Yunhe Wang, Xinghao Chen, Chang Xu
Conference on Neural Information Processing Systems (NeurIPS), 2021
Towards stable and robust addernets
Minjing Dong, Yunhe Wang, Xinghao Chen, Chang Xu
Conference on Neural Information Processing Systems (NeurIPS), 2021
Neural architecture search in a proxy validation loss landscape
Yanxi Li, Minjing Dong, Yunhe Wang, Chang Xu
International Conference on Machine Learning (ICML), 2020
Adversarial recurrent time series imputation
Shuo Yang, Minjing Dong, Yunhe Wang, Chang Xu
IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2020
Crafting Efficient Neural Graph of Large Entropy
Minjing Dong, Hanting Chen, Yunhe Wang, Chang Xu
International Joint Conference on Artificial Intelligence (IJCAI), 2019
On Retrospecting Human Dynamics with Attention
Minjing Dong, Chang Xu
International Joint Conference on Artificial Intelligence (IJCAI), 2019
🏆 Awards
- 2024, Best PhD Thesis Award, University of Sydney
- 2023, AAAI-23 Distinguished Paper Award (12/8777)
- 2020, Faculty of Engineering Research Scholarship, University of Sydney
📖 Teaching
- 2024, Lecturer, CS1302: Introduction to Computer Programming, City University of Hong Kong
- 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
- 2024, Organizer of Tutorial “Efficient_and_Secure_Foundation_Models”, IJCNN 2024
- 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: Aug 07, 2024