Overview
Background
Yadan Luo is currently a Lecturer with Data Science Discipline, School of ITEE, The University of Queensland. She received her BSc degree from University of Electronic Science and Technology of China, and her PhD in Computer Science from School of ITEE, The University of Queensland in 2017 and 2021 respectively. Her research interests mainly include machine learning from imperfect data, by leveraging domain adaptation, domain generalization, few-/zero-shot learning and active learning to empower the applications in computer vision and multimedia data analysis areas. Her work of image analysis published at Pattern Recognition Journal in 2018 is placed in the top 1% of the academic field of Engineering and is recognised as a Highly Cited Paper by Web of Science. Yadan was awarded the Google PhD Fellowship 2020 as a recognition of her research in the machine learning area and her strong potential of influencing the future of technology. She was also a recipient of ICT Young Achiever Award, Women in Technology (WiT.org) 2018 and a few other research awards.
[For Prospective Students] I am continuously looking for highly-motivated Ph.D. students to work on machine learning & multimedia data analysis, specifically for addressing domain shifts and generalisation issues. Please send me your CV if interested.
Availability
- Dr Yadan Luo is:
- Available for supervision
- Media expert
Qualifications
- Bachelor of Computer Science, University of Electronic Science and Technology of China
- Doctor of Philosophy, The University of Queensland
Research interests
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Multimedia Data Analysis
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Machine Learning
Domain adaptation, domain generalization
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3D Lidar-based Object Detection
Works
Search Professor Yadan Luo’s works on UQ eSpace
Featured
2023
Journal Article
Source-free progressive graph learning for open-set domain adaptation
Luo, Yadan, Wang, Zijian, Chen, Zhuoxiao, Huang, Zi and Baktashmotlagh, Mahsa (2023). Source-free progressive graph learning for open-set domain adaptation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 45 (9), 1-16. doi: 10.1109/tpami.2023.3270288
Featured
2021
Journal Article
Interpretable signed link prediction with signed infomax hyperbolic graph
Luo, Yadan, Huang, Zi, Chen, Hongxu, Yang, Yang, Yin, Hongzhi and Baktashmotlagh, Mahsa (2021). Interpretable signed link prediction with signed infomax hyperbolic graph. IEEE Transactions on Knowledge and Data Engineering, PP (99), 1-1. doi: 10.1109/TKDE.2021.3139035
2021
Conference Publication
Discovering collaborative signals for next POI recommendation with iterative Seq2Graph augmentation
Li, Yang, Chen, Tong, Luo, Yadan, Yin, Hongzhi and Huang, Zi (2021). Discovering collaborative signals for next POI recommendation with iterative Seq2Graph augmentation. Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, Montreal, QC Canada, 19 - 27 August 2021. Palo Alto, CA United States: A A A I Press. doi: 10.24963/ijcai.2021/206
Featured
2020
Conference Publication
Learning from the past: continual meta-learning with Bayesian Graph Neural Networks
Luo, Yadan, Huang, Zi, Zhang, Zheng, Wang, Ziwei, Baktashmotlagh, Mahsa and Yang, Yang (2020). Learning from the past: continual meta-learning with Bayesian Graph Neural Networks. The Thirty-Fourth AAAI Conference on Artificial Intelligence/ The Thirty-Second Conference on Innovative Applications of Artificial Intelligence/ The Tenth Symposium on Educational Advances in Artificial Intelligence, New York, United States, 7-12 February 2020. Palo Alto, CA, United States: Association for the Advancement of Artificial Intelligence (AAAI). doi: 10.1609/aaai.v34i04.5942
Featured
2020
Conference Publication
Progressive graph learning for open-set domain adaptation
Luo, Yadan, Wang, Zijian, Huang, Zi and Baktashmotlagh, Mahsa (2020). Progressive graph learning for open-set domain adaptation. 37th International Conference on Machine Learning ICML 2020, Vienna, Austria, 12-18 July 2020 . International Machine Learning Society .
2024
Conference Publication
ConjNorm: tractable density estimation for out-of-distribution detection
Peng, Bo, Luo, Yadan, Zhang, Yonggang, Li, Yixuan and Fang, Zhen (2024). ConjNorm: tractable density estimation for out-of-distribution detection. 12th International Conference on Learning Representations, ICLR 2024, Vienna, Austria, 7-11 May 2024. Vienna, Austria: International Conference on Learning Representations, ICLR.
2024
Journal Article
Out-of-distribution detection with virtual outlier smoothing
Nie, Jun, Luo, Yadan, Ye, Shanshan, Zhang, Yonggang, Tian, Xinmei and Fang, Zhen (2024). Out-of-distribution detection with virtual outlier smoothing. International Journal of Computer Vision. doi: 10.1007/s11263-024-02210-8
2024
Conference Publication
Optimizing taxi route planning based on taxi trajectory data analysis
Yang, Xinyi, Chen, Zhi and Luo, Yadan (2024). Optimizing taxi route planning based on taxi trajectory data analysis. 34th Australasian Database Conference (ADC), Melbourne, VIC, Australia, 1-3 November 2023. Heidelberg, Germany: Springer. doi: 10.1007/978-3-031-47843-7_4
2023
Conference Publication
Learning efficient unsupervised satellite image-based building damage detection
Zhang, Yiyun, Wang, Zijian, Luo, Yadan, Yu, Xin and Huang, Zi (2023). Learning efficient unsupervised satellite image-based building damage detection. 2023 IEEE International Conference on Data Mining (ICDM), Shanghai, China, 1-4 December 2023. Piscataway, NJ, United States: IEEE. doi: 10.1109/icdm58522.2023.00206
2023
Conference Publication
Cal-SFDA: Source-free domain-adaptive semantic segmentation with differentiable expected calibration error
Wang, Zixin, Luo, Yadan, Chen, Zhi, Wang, Sen and Huang, Zi (2023). Cal-SFDA: Source-free domain-adaptive semantic segmentation with differentiable expected calibration error. MM '23: The 31st ACM International Conference on Multimedia, Ottawa, ON Canada, 29 October - 3 November 2023. New York, NY United States: Association for Computing Machinery. doi: 10.1145/3581783.3611808
2023
Conference Publication
Open-RoadAtlas: Leveraging VLMs for road condition survey with real-time mobile auditing
Etchegaray, Djamahl, Luo, Yadan, FitzChance, Zachary, Southon, Anthony and Zhong, Jinjiang (2023). Open-RoadAtlas: Leveraging VLMs for road condition survey with real-time mobile auditing. MM '23: The 31st ACM International Conference on Multimedia, Ottawa, ON Canada, 29 October - 3 November 2023. New York, NY United States: Association for Computing Machinery. doi: 10.1145/3581783.3612668
2023
Conference Publication
Revisiting Domain-Adaptive 3D Object Detection by Reliable, Diverse and Class-balanced Pseudo-Labeling
Chen, Zhuoxiao, Luo, Yadan, Wang, Zheng, Baktashmotlagh, Mahsa and Huang, Zi (2023). Revisiting Domain-Adaptive 3D Object Detection by Reliable, Diverse and Class-balanced Pseudo-Labeling. IEEE/CVF International Conference on Computer Vision 2023 (ICCV), Paris, France, 2-6 October 2023. Paris, France: Computer Vision Foundation. doi: 10.1109/iccv51070.2023.00344
2023
Conference Publication
How Far Pre-trained Models Are from Neural Collapse on the Target Dataset Informs their Transferability
Wang, Zijian, Luo, Yadan, Zheng, Liang, Huang, Zi and Baktashmotlagh, Mahsa (2023). How Far Pre-trained Models Are from Neural Collapse on the Target Dataset Informs their Transferability. IEEE/CVF International Conference on Computer Vision 2023 (ICCV), Paris, France, 2-6 October 2023. Paris, France: Computer Vision Foundation. doi: 10.1109/iccv51070.2023.00511
2023
Conference Publication
KECOR: Kernel Coding Rate Maximization for Active 3D Object Detection
Luo, Yadan, Chen, Zhuoxiao, Fang, Zhen, Zhang, Zheng, Baktashmotlagh, Mahsa and Huang, Zi (2023). KECOR: Kernel Coding Rate Maximization for Active 3D Object Detection. IEEE/CVF International Conference on Computer Vision 2023 (ICCV), Paris, France, 2-6 October 2021. Paris, France: Computer Vision Foundation. doi: 10.1109/iccv51070.2023.01676
2023
Journal Article
Hypercomplex context guided interaction modeling for scene graph generation
Wang, Zheng, Xu, Xing, Luo, Yadan, Wang, Guoqing and Yang, Yang (2023). Hypercomplex context guided interaction modeling for scene graph generation. Pattern Recognition, 141 109634, 109634. doi: 10.1016/j.patcog.2023.109634
2023
Journal Article
Deep collaborative graph hashing for discriminative image retrieval
Zhang, Zheng, Wang, Jianning, Zhu, Lei, Luo, Yadan and Lu, Guangming (2023). Deep collaborative graph hashing for discriminative image retrieval. Pattern Recognition, 139 109462, 1-14. doi: 10.1016/j.patcog.2023.109462
2023
Conference Publication
Exploring active 3D object detection from a generalization perspective
Luo, Yadan, Chen, Zhuoxiao, Wang, Zijian, Yu, Xin, Huang, Zi and Baktashmotlagh, Mahsa (2023). Exploring active 3D object detection from a generalization perspective. 11th International Conference on Learning Representations (ICLR), Kigali, Rwanda, 1 - 5 May 2023. New York, NY, United States: Cornell Tech. doi: 10.48550/arXiv.2301.09249
2023
Journal Article
GSMFlow: generation shifts mitigating flow for generalized zero-shot learning
Chen, Zhi, Luo, Yadan, Wang, Sen, Li, Jingjing and Huang, Zi (2023). GSMFlow: generation shifts mitigating flow for generalized zero-shot learning. IEEE Transactions on Multimedia, 25 (99), 5374-5385. doi: 10.1109/tmm.2022.3190678
2023
Conference Publication
FFM: injecting out-of-domain knowledge via factorized frequency modification
Wang, Zijian, Luo, Yadan, Huang, Zi and Baktashmotlagh, Mahsa (2023). FFM: injecting out-of-domain knowledge via factorized frequency modification. 23rd IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), Waikoloa, HI, United States, 3-7 January 2023. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/wacv56688.2023.00412
2022
Conference Publication
Point to rectangle matching for image text retrieval
Wang, Zheng, Gao, Zhenwei, Xu, Xing, Luo, Yadan, Yang, Yang and Shen, Heng Tao (2022). Point to rectangle matching for image text retrieval. 30th ACM International Conference on Multimedia, Lisbon, Portugal, 10-14 October 2022. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3503161.3548237
Funding
Current funding
Supervision
Availability
- Dr Yadan Luo is:
- Available for supervision
Before you email them, read our advice on how to contact a supervisor.
Supervision history
Current supervision
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Doctor Philosophy
Towards Open-vocabulary 3D Object Detection
Principal Advisor
Other advisors: Professor Helen Huang
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Doctor Philosophy
Unsupervised Domain Adaptation on 3D Object Detection and Segmentation
Principal Advisor
Other advisors: Professor Helen Huang, Dr Mahsa Baktashmotlagh
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Doctor Philosophy
Maximizing Object Detection Dataset Efficiency through the Power of Active Learning
Principal Advisor
Other advisors: Professor Helen Huang
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Doctor Philosophy
Multimodal Sensing System for 3D Vision
Principal Advisor
Other advisors: Professor Helen Huang
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Doctor Philosophy
Towards Explainable Multi-source Multivariate Time-series Analysis
Associate Advisor
Other advisors: Professor Helen Huang, Associate Professor Sen Wang
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Doctor Philosophy
Developing efficient and stable perovskite quantum dot light emitting diodes
Associate Advisor
Other advisors: Professor Lianzhou Wang
Completed supervision
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2023
Doctor Philosophy
Monocular 3D Reconstruction: Shape Representation, Scalability and Generalization.
Associate Advisor
Other advisors: Dr Mahsa Baktashmotlagh
Media
Enquiries
Contact Dr Yadan Luo directly for media enquiries about their areas of expertise.
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