Overview
Background
Yadan Luo is currently a Senior Lecturer with Data Science Discipline, School of EECS, 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
2024
Conference Publication
Color-oriented redundancy reduction in dataset distillation
Yuan, Bowen, Wang, Zijian, Baktashmotlagh, Mahsa, Luo, Yadan and Huang, Zi (2024). Color-oriented redundancy reduction in dataset distillation. Thirty-eighth Annual Conference on Neural Information Processing Systems, Vancouver, BC, Canada, 10 - 15 December 2024. Maryland Heights, MO, United States: Morgan Kaufmann Publishers.
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
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
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
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
Interpretable signed link prediction with signed infomax hyperbolic graph
Luo, Yadan, Huang, Zi, Chen, Hongxu, Yang, Yang, Yin, Hongzhi and Baktashmotlagh, Mahsa (2023). Interpretable signed link prediction with signed infomax hyperbolic graph. IEEE Transactions on Knowledge and Data Engineering, 35 (4), 3991-4002. doi: 10.1109/TKDE.2021.3139035
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
2022
Conference Publication
FluMA: An Intelligent Platform for Influenza Monitoring and Analysis
Chen, Xi, Chen, Zhi, Wang, Zijian, Qiu, Ruihong and Luo, Yadan (2022). FluMA: An Intelligent Platform for Influenza Monitoring and Analysis. 33rd Australasian Database Conference (ADC), Sydney, NSW Australia, 2-4 September 2022. Heidelberg, Germany: Springer. doi: 10.1007/978-3-031-15512-3_12
2022
Conference Publication
Discovering domain disentanglement for generalized multi-source domain adaptation
Wang, Zixin, Luo, Yadan, Zhang, Peng-Fei, Wang, Sen and Huang, Zi (2022). Discovering domain disentanglement for generalized multi-source domain adaptation. 2022 IEEE International Conference on Multimedia and Expo (ICME), Taipei, Taiwan, 18-22 July 2022. Piscataway, NJ United States: IEEE Computer Society. doi: 10.1109/icme52920.2022.9859733
2021
Conference Publication
Conditional Extreme Value Theory for Open Set Video Domain Adaptation
Chen, Zhuoxiao, Luo, Yadan and Baktashmotlagh, Mahsa (2021). Conditional Extreme Value Theory for Open Set Video Domain Adaptation. MMAsia '21: ACM Multimedia Asia, Gold Coast, QLD Australia, 1 - 3 December 2021. New York, NY United States: Association for Computing Machinery. doi: 10.1145/3469877.3490600
2021
Journal Article
Collaborative learning for extremely low bit asymmetric hashing
Luo, Yadan, Huang, Zi, Li, Yang, Shen, Fumin, Yang, Yang and Cui, Peng (2021). Collaborative learning for extremely low bit asymmetric hashing. IEEE Transactions on Knowledge and Data Engineering, 33 (12), 3675-3685. doi: 10.1109/tkde.2020.2977633
2021
Conference Publication
RoadAtlas: intelligent platform for automated road defect detection and asset management
Chen, Zhuoxiao, Zhang, Yiyun, Luo, Yadan, Wang, Zijian, Zhong, Jinjiang and Southon, Anthony (2021). RoadAtlas: intelligent platform for automated road defect detection and asset management. MMAsia '21: ACM Multimedia Asia, Gold Coast, QLD Australia, 1 - 3 December 2021. New York, NY United States: Association for Computing Machinery. doi: 10.1145/3469877.3493589
2021
Conference Publication
Mitigating Generation Shifts for Generalized Zero-Shot Learning
Chen, Zhi, Luo, Yadan, Wang, Sen, Qiu, Ruihong, Li, Jingjing and Huang, Zi (2021). Mitigating Generation Shifts for Generalized Zero-Shot Learning. MM '21: ACM Multimedia Conference, Online, 20 - 24 October 2021. Washington, DC United States: Association for Computing Machinery. doi: 10.1145/3474085.3475258
Funding
Current funding
Past funding
Supervision
Availability
- Dr Yadan Luo is:
- Available for supervision
Looking for a supervisor? Read our advice on how to choose a supervisor.
Supervision history
Current supervision
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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 Open-vocabulary 3D Object Detection
Principal Advisor
Other advisors: Professor Helen Huang
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Doctor Philosophy
Information Dissemination Prediction for Emerging Video Sharing Platforms
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, Associate Professor Mahsa Baktashmotlagh
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Doctor Philosophy
Data-Centric Advancements in Neural Radiance Fields for 3D Reconstruction
Principal Advisor
Other advisors: Professor Helen Huang
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Doctor Philosophy
Enhancing Safety and Reliability of machine learning models using lifelong multi-modal learning
Associate Advisor
Other advisors: Professor Helen Huang, Associate Professor Mahsa Baktashmotlagh
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Doctor Philosophy
Active Learning for Multi-modal 3D Perception
Associate Advisor
Other advisors: Professor Helen Huang
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Doctor Philosophy
Foundation-Model-Guided Gaussian Modelling for Immersive 3D Scene Simulation
Associate Advisor
Other advisors: Professor Helen Huang
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Doctor Philosophy
Enhancing Plant Phenotyping Accuracy through Analysing Video Data
Associate Advisor
Other advisors: Professor Scott Chapman, Associate Professor Mahsa Baktashmotlagh
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Doctor Philosophy
Multimodal Representation Learning for Responsive Video-sharing Services
Associate Advisor
Other advisors: Professor Helen Huang
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Doctor Philosophy
Advancing Embodied Visual Content understanding through Egocentric Videos
Associate Advisor
Other advisors: Professor Helen Huang
Completed supervision
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2025
Doctor Philosophy
Developing Efficient and Stable Perovskite Quantum Dot Light Emitting Diodes
Associate Advisor
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2025
Doctor Philosophy
Towards Practical Adaptation to Domain Shift in Deep Vision Learning
Associate Advisor
Other advisors: Professor Helen Huang, Associate Professor Sen Wang
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2023
Doctor Philosophy
Monocular 3D Reconstruction: Shape Representation, Scalability and Generalization.
Associate Advisor
Other advisors: Associate Professor Mahsa Baktashmotlagh
Media
Enquiries
Contact Dr Yadan Luo directly for media enquiries about their areas of expertise.
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