Mingming Gong
Affiliated Associate Professor of Machine Learning
Research interests
Gong works on the theoretical foundations and computational innovations in causal structure learning from real-world complex data. He explores causal principles to tackle challenges in machine learning, such as transferability, robustness, and interpretability. On the application side, he develops machine learning algorithms to solve real-world problems in computer vision, biomedical science, robotics, etc. Email
Gong is currently a senior lecturer at the School of Mathematics and Statistics, University of Melbourne, Australia, and a Principal Investigator at the Melbourne Centre for Data Science. He was awarded the Discovery Early Career Research Award from Australian Research Council in 2021.
He received the research excellence scholarship during his master’s study at Nanjing University, China. Gong then received a university chancellor's scholarship to pursue a Ph.D. at the University of Technology Sydney. Following his Ph.D., he undertook a joint postdoc position with University of Pittsburgh and Carnegie Mellon University.
Gong has served as the area chair for top conferences such as International Conference on Machine Learning (ICML), the Conference and Workshop on Neural Information Processing Systems (NeurIPS), the International Conference on Learning Representations (ICLR), and the Conference on Uncertainty in Artificial Intelligence UAI. His research work on depth estimation won the first-prize at CVPR 2018 robust vision challenge, and his work on unsupervised domain mapping was a CVPR 2019 best paper finalist. He interned at Max Planck Institute for Intelligent Systems in German.
- Bachelor in electronic information science and technology from Nanjing University, China
- Master’s in communications and information system from Huazhong University of Science and Technology, China
- Ph.D. in information technology from University of Technology Sydney, Australia
- Postdoc in machine learning from University of Pittsburgh and Carnegie Mellon University, USA
- ARC Discovery Early Career Research Award Grant
- CCF-Tencent Rhino-Bird Young Faculty Open Research Fund
- Global Top Chinese Young Scholar in Artificial Intelligence (by Baidu Academic)
- IJCAI 2020 early career spotlight
- CVPR 2019 best paper finalist (top 1%)
- 1st place in CVPR Robust Vision Challenge, 2018
Gong has authored and co-authored 50-plus research papers at top conferences such as ICML, NeurIPS, UAI, CVPR, etc.
- Dongting Hu, Liuhua Peng, Tingjin Chu, Xiaoxing Zhang, Yinian Mao, Howard Bondell, Mingming Gong: Uncertainty Quantification in Depth Estimation via Constrained Ordinal Regression. Proceedings of European Conference on Computer Vision (ECCV), Tel Aviv, Israel, 2022.
- Jian Zhang*, Jinchi Huang*, Bowen Cai*, Mingming Gong, Chaohui Wang, Jiaming Wang, Hongchen Luo, Rongfei Jia, Binqiang Zhao, Xing Tang, Huan Fu: Digging into Radiance Grid for Real-Time View Synthesis with Detail Preservation. Proceedings of European Conference on Computer Vision (ECCV), Tel Aviv, 2022.
- Yanwu Xu, Shaoan Xie, Maxwell Reynolds, Matthew Ragoza, Mingming Gong*, Kayhan Batmanghelich*: Adversarial Consistency for Single Domain Generalization in Medical Image Segmentation. Proceedings of International Conference on 25th Medical Image Computing and Computer Assisted Intervention (MICCAI), Singapore, 2022.
- Chaojian Yu, Bo Han, Li Shen, Jun Yu, Chen Gong, Mingming Gong, Tongliang Liu: Understanding Robust Overfitting of Adversarial Training and Beyond. Proceedings of the 38th International Conference on Machine Learning (ICML), Baltimore, Maryland, USA, 2022.
- Xiaobo Xia*, Shuo Shan*, Mingming Gong, Nannan Wang, Fei Gao, Haikun Wei, Tongliang Liu: Sample-Efficient Kernel Mean Estimator with Marginalized Corrupted Data. Proceedings of SIGKDD Con- ference on Knowledge Discovery and Data Mining (KDD), Washington DC, USA, 2022.
- Chaojian Yu, Bo Han, Mingming Gong, Li Shen, Shiming Ge, Bo Du, Tongliang Liu: Robust Weight Per- turbation for Adversarial Training. Proceedings of International Joint Conference on Artificial Intelligence (IJCAI), Messe Wien, Vienna, Austria, 2022.
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