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Dr Yadan Luo
Dr

Yadan Luo

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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

  • Multimedia Data Analysis

  • Machine Learning

    Domain adaptation, domain generalization

  • 3D Lidar-based Object Detection

Works

Search Professor Yadan Luo’s works on UQ eSpace

83 works between 2016 and 2026

41 - 60 of 83 works

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

How Far Pre-trained Models Are from Neural Collapse on the Target Dataset Informs their Transferability

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

Hypercomplex context guided interaction modeling for scene graph generation

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

Deep collaborative graph hashing for discriminative image retrieval

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

Exploring active 3D object detection from a generalization perspective

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

Interpretable signed link prediction with signed infomax hyperbolic graph

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

FFM: injecting out-of-domain knowledge via factorized frequency modification

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

GSMFlow: generation shifts mitigating flow for generalized zero-shot learning

2022

Journal Article

Photodegradation of biobased polymer blends in seawater: a major source of microplastics in the marine environment

Zhao, Shasha, Liu, Liuqingqing, Li, Chenguang, Zheng, Hao, Luo, Yadan, Pang, Lihua, Lin, Qianhui, Zhang, Hongyu, Sun, Cuizhu, Chen, Lingyun and Li, Fengmin (2022). Photodegradation of biobased polymer blends in seawater: a major source of microplastics in the marine environment. Frontiers in Marine Science, 9 1046179. doi: 10.3389/fmars.2022.1046179

Photodegradation of biobased polymer blends in seawater: a major source of microplastics in the marine environment

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

Point to rectangle matching for image text retrieval

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

FluMA: An Intelligent Platform for Influenza Monitoring and Analysis

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

Discovering domain disentanglement for generalized multi-source domain adaptation

2022

Journal Article

Spatial patterns of microplastics in surface seawater, sediment, and sand along Qingdao coastal environment

Luo, Yadan, Sun, Cuizhu, Li, Chenguang, Liu, Yifan, Zhao, Shasha, Li, Yuanyuan, Kong, Fanna, Zheng, Hao, Luo, Xianxiang, Chen, Lingyun and Li, Fengmin (2022). Spatial patterns of microplastics in surface seawater, sediment, and sand along Qingdao coastal environment. Frontiers in Marine Science, 9 916859. doi: 10.3389/fmars.2022.916859

Spatial patterns of microplastics in surface seawater, sediment, and sand along Qingdao coastal environment

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

Conditional Extreme Value Theory for Open Set Video Domain Adaptation

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

Collaborative learning for extremely low bit asymmetric hashing

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

RoadAtlas: intelligent platform for automated road defect detection and asset management

2021

Conference Publication

Semantics disentangling for generalized zero-shot learning

Chen, Zhi, Luo, Yadan, Qiu, Ruihong, Wang, Sen, Huang, Zi, Li, Jingjing and Zhang, Zheng (2021). Semantics disentangling for generalized zero-shot learning. 2021 IEEE/CVF International Conference on Computer Vision (ICCV), Montreal, QC Canada, 10-17 October 2021. Piscataway, NJ USA: Institute of Electrical and Electronics Engineers. doi: 10.1109/iccv48922.2021.00859

Semantics disentangling for generalized zero-shot learning

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

Mitigating Generation Shifts for Generalized Zero-Shot Learning

2021

Other Outputs

Visual learning from imperfect data via inductive bias modelling

Luo, Yadan (2021). Visual learning from imperfect data via inductive bias modelling. PhD Thesis, School of Information Technology and Electrical Engineering, The University of Queensland. doi: 10.14264/bd5d3e6

Visual learning from imperfect data via inductive bias modelling

2021

Journal Article

High-order nonlocal Hashing for unsupervised cross-modal retrieval

Zhang, Peng-Fei, Luo, Yadan, Huang, Zi, Xu, Xin-Shun and Song, Jingkuan (2021). High-order nonlocal Hashing for unsupervised cross-modal retrieval. World Wide Web, 24 (2), 563-583. doi: 10.1007/s11280-020-00859-y

High-order nonlocal Hashing for unsupervised cross-modal retrieval

2021

Conference Publication

Learning to diversify for single domain generalization

Wang, Zijian, Luo, Yadan, Qiu, Ruihong, Huang, Zi and Baktashmotlagh, Mahsa (2021). Learning to diversify for single domain generalization. 2021 IEEE/CVF International Conference on Computer Vision (ICCV), Montreal, QC Canada, 10-17 October 2021. Piscataway, NJ USA: Institute of Electrical and Electronics Engineers. doi: 10.1109/ICCV48922.2021.00087

Learning to diversify for single domain generalization

Funding

Current funding

  • 2024 - 2027
    Towards Evolvable and Sustainable Multimodal Machine Learning
    ARC Discovery Early Career Researcher Award
    Open grant
  • 2024 - 2027
    Embracing Changes for Responsive Video-sharing Services
    ARC Discovery Projects
    Open grant
  • 2023 - 2027
    Analytics for the Australian Grains Industry (AAGI)
    Grains Research & Development Corporation
    Open grant

Past funding

  • 2025
    Beating the Neural Scaling Law through Affordable Machine Learning
    UQ Foundation Research Excellence Awards
    Open grant
  • 2023 - 2026
    Road Atlas: AI-power platform for automated road distress detection and asset management
    Logan City Council
    Open grant
  • 2022 - 2024
    Developing a proof-of-concept self-contact tracing app to support epidemiological investigations and outbreak response (Australia-Korea Joint Call for Joint Research Projects - ATSE Tech Bridge Grant)
    Australian Academy of Technological Sciences and Engineering
    Open grant

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

  • Doctor Philosophy

    Multimodal Sensing System for 3D Vision

    Principal Advisor

    Other advisors: Professor Helen Huang

  • Doctor Philosophy

    Maximizing Object Detection Dataset Efficiency through the Power of Active Learning

    Principal Advisor

    Other advisors: Professor Helen Huang

  • Doctor Philosophy

    Data-Centric Advancements in Neural Radiance Fields for 3D Reconstruction

    Principal Advisor

    Other advisors: Professor Helen Huang

  • Doctor Philosophy

    Towards Open-Vocabulary Scene Understanding

    Principal Advisor

    Other advisors: Professor Helen Huang

  • Doctor Philosophy

    Information Dissemination Prediction for Emerging Video Sharing Platforms

    Principal Advisor

    Other advisors: Professor Helen Huang

  • Doctor Philosophy

    Enhancing Plant Phenotyping Accuracy through Analysing Video Data

    Associate Advisor

    Other advisors: Professor Scott Chapman, Associate Professor Mahsa Baktashmotlagh

  • Doctor Philosophy

    Multimodal Representation Learning for Responsive Video-sharing Services

    Associate Advisor

    Other advisors: Professor Helen Huang

  • Doctor Philosophy

    Foundation-Model-Guided Gaussian Modelling for Immersive 3D Scene Simulation

    Associate Advisor

    Other advisors: Professor Helen Huang

  • Doctor Philosophy

    Controlling Knowledge Dynamics in Pre-trained Deep Neural Networks

    Associate Advisor

    Other advisors: Professor Helen Huang, Associate Professor Mahsa Baktashmotlagh

  • Doctor Philosophy

    Adaptive Human-Robot Interaction for Unstructured, Dynamic Environments with Rich Physical Interactions

    Associate Advisor

    Other advisors: Associate Professor Jen Jen Chung

  • Doctor Philosophy

    Advancing Embodied Visual Content understanding through Egocentric Videos

    Associate Advisor

    Other advisors: Professor Helen Huang

Completed supervision

Media

Enquiries

Contact Dr Yadan Luo directly for media enquiries about their areas of expertise.

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