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Dr Yadan Luo
Dr

Yadan Luo

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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

  • Multimedia Data Analysis

  • Machine Learning

    Domain adaptation, domain generalization

  • 3D Lidar-based Object Detection

Works

Search Professor Yadan Luo’s works on UQ eSpace

51 works between 2016 and 2024

21 - 40 of 51 works

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

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

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

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

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

2020

Conference Publication

Adversarial bipartite graph learning for video domain adaptation

Luo, Yadan, Huang, Zi, Wang, Zijian, Zhang, Zheng and Baktashmotlagh, Mahsa (2020). Adversarial bipartite graph learning for video domain adaptation. ACM International Conference on Multimedia, Seattle, WA, United States, 12-16 October 2020. New York, United States: Association for Computing Machinery. doi: 10.1145/3394171.3413897

Adversarial bipartite graph learning for video domain adaptation

2020

Conference Publication

Prototype-matching graph network for heterogeneous domain adaptation

Wang, Zijian, Luo, Yadan, Huang, Zi and Baktashmotlagh, Mahsa (2020). Prototype-matching graph network for heterogeneous domain adaptation. MM '20: 28th ACM International Conference on Multimedia, Online, October 2020. New York, NY, United States: ACM. doi: 10.1145/3394171.3413662

Prototype-matching graph network for heterogeneous domain adaptation

2020

Conference Publication

Human consensus-oriented image captioning

Wang, Ziwei, Huang, Zi and Luo, Yadan (2020). Human consensus-oriented image captioning. Twenty-Ninth International Joint Conference on Artificial Intelligence, Yokohama, Japan, 7-15 January 2021. Palo Alto, CA, United States: AAAI Press. doi: 10.24963/ijcai.2020/92

Human consensus-oriented image captioning

2020

Journal Article

Deep collaborative discrete hashing with semantic-invariant structure construction

Wang, Zijian, Zhang, Zheng, Luo, Yadan, Huang, Zi and Shen, Heng Tao (2020). Deep collaborative discrete hashing with semantic-invariant structure construction. IEEE Transactions on Multimedia, 23 9096547, 1274-1286. doi: 10.1109/tmm.2020.2995267

Deep collaborative discrete hashing with semantic-invariant structure construction

2020

Conference Publication

CANZSL: Cycle-consistent adversarial networks for zero-shot learning from natural language

Chen, Zhi, Li, Jingjing, Luo, Yadan, Huang, Zi and Yangyang, Yangyang (2020). CANZSL: Cycle-consistent adversarial networks for zero-shot learning from natural language. IEEE Winter Conference on Applications of Computer Vision (WACV), Snowmass, CO United States, 1-5 March 2020. Piscataway, NJ United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/WACV45572.2020.9093610

CANZSL: Cycle-consistent adversarial networks for zero-shot learning from natural language

2020

Conference Publication

Graph-based relation-aware representation learning for clothing matching

Li, Yang, Luo, Yadan and Huang, Zi (2020). Graph-based relation-aware representation learning for clothing matching. Australasian Database Conference, Melbourne, VIC, Australia, 3-7 February 2020. Cham, Switzerland: Springer. doi: 10.1007/978-3-030-39469-1_15

Graph-based relation-aware representation learning for clothing matching

2020

Conference Publication

PAIC: Parallelised Attentive Image Captioning

Wang, Ziwei, Huang, Zi and Luo, Yadan (2020). PAIC: Parallelised Attentive Image Captioning. 31st Australasian Database Conference, ADC 2020, Melbourne, VIC, Australia, February 3–7, 2020. Cham, Switzerland: Springer International Publishing. doi: 10.1007/978-3-030-39469-1_2

PAIC: Parallelised Attentive Image Captioning

2020

Journal Article

Inductive structure consistent hashing via flexible semantic calibration

Zhang, Zheng, Liu, Luyao, Luo, Yadan, Huang, Zi, Shen, Fumin, Shen, Heng Tao and Lu, Guangming (2020). Inductive structure consistent hashing via flexible semantic calibration. IEEE Transactions on Neural Networks and Learning Systems, 32 (10), 1-15. doi: 10.1109/tnnls.2020.3018790

Inductive structure consistent hashing via flexible semantic calibration

2020

Conference Publication

Fashion recommendation with multi-relational representation learning

Li, Yang, Luo, Yadan and Huang, Zi (2020). Fashion recommendation with multi-relational representation learning. 24th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2020, Singapore, 11-14 May 2020. Heidelberg, Germany: Springer. doi: 10.1007/978-3-030-47426-3_1

Fashion recommendation with multi-relational representation learning

2020

Conference Publication

Semi-supervised cross-modal hashing with graph convolutional networks

Duan, Jiasheng, Luo, Yadan, Wang, Ziwei and Huang, Zi (2020). Semi-supervised cross-modal hashing with graph convolutional networks. Australasian Database Conference, Melbourne, VIC, Australia, 3-7 February 2020. Cham, Switzerland: Springer. doi: 10.1007/978-3-030-39469-1_8

Semi-supervised cross-modal hashing with graph convolutional networks

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 - 2026
    Road Atlas: AI-power platform for automated road distress detection and asset management
    Logan City Council
    Open grant
  • 2023 - 2027
    Analytics for the Australian Grains Industry (AAGI)
    Grains Research & Development Corporation
    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

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Supervision history

Current supervision

Completed supervision

Media

Enquiries

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