Dr Yadan Luo

Lecturer

School of Electrical Engineering and Computer Science
Faculty of Engineering, Architecture and Information Technology

Overview

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.

Research Interests

  • Multimedia Data Analysis
  • Machine Learning
    Domain adaptation, domain generalization
  • 3D Lidar-based Object Detection

Qualifications

  • Doctor of Philosophy, The University of Queensland
  • Bachelor of Computer Science, University of Electronic Science and Technology of China

Publications

  • 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

  • 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

  • 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

  • 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

  • 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 .

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Grants

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Supervision

  • Doctor Philosophy

  • Doctor Philosophy

  • Doctor Philosophy

View all Supervision

Publications

Featured Publications

  • 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

  • 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

  • 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

  • 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

  • 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 .

Journal Article

Conference Publication

  • 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. New York, NY, USA: ACM. doi: 10.1145/3581783.3611808

  • 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. New York, NY, USA: ACM. doi: 10.1145/3581783.3612668

  • 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

  • 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

  • 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

  • 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

  • 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

  • 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

  • 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

  • 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

  • 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

  • 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

  • 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

  • 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

  • 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

  • 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

  • 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

  • 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

  • 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

  • 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

  • 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

  • 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

  • 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

  • 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

  • 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 .

  • 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

  • Tong, Yuzhen, Luo, Yadan, Zhang, Zheng, Sadiq, Shazia and Cui, Peng (2019). Collaborative generative adversarial network for recommendation systems. 2019 IEEE 35th International Conference on Data Engineering Workshops (ICDEW), Macao, 8-12 April 2019. Piscataway, NJ United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/ICDEW.2019.00-16

  • Li, Yang, Luo, Yadan, Zhang, Zheng, Sadiq, Shazia and Cui, Peng (2019). Context-aware attention-based data augmentation for POI recommendation. 2019 IEEE 35th International Conference on Data Engineering Workshops (ICDEW), Macao, 8-12 April 2019. Piscataway, NJ United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/ICDEW.2019.00-14

  • Luo, Yadan, Huang, Zi, Zhang, Zheng, Wang, Ziwei, Li, Jingjing and Yang, Yang (2019). Curiosity-driven reinforcement learning for diverse visual paragraph generation. 27th ACM International Conference on Multimedia (MM), Nice, France, 21-25 October 2019. New York, NY United States: Association for Computing Machinery. doi: 10.1145/3343031.3350961

  • Chen, Zhi and Luo, Yadan (2019). Cycle-consistent diverse image synthesis from natural language. 2019 IEEE International Conference on Multimedia and Expo Workshops (ICMEW), Shanghai, China, 8-12 July 2019. Piscataway, NJ, United States: IEEE. doi: 10.1109/icmew.2019.00085

  • Wang, Zijian, Luo, Yadan, Zhang, Zheng and Huang, Zi (2019). Deep collaborative discrete hashing with semantic-invariant structure. 42nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), Paris, France, 21-25 July 2019. New York, NY United States: Association for Computing Machinery. doi: 10.1145/3331184.3331275

  • Luo, Yadan, Wang, Ziwei, Huang, Zi, Yang, Yang and Zhao, Cong (2018). Coarse-to-fine annotation enrichment for semantic segmentation learning. 27th ACM International Conference on Information and Knowledge Management, CIKM 2018, Torino, Italy, 22-26 October 2018. New York, NY United States: Association for Computing Machinery. doi: 10.1145/3269206.3271672

  • Wang, Ziwei, Luo, Yadan, Li, Yang, Huang, Zi and Yin, Hongzhi (2018). Look deeper see richer: Depth-aware image paragraph captioning. 26th ACM Multimedia conference, MM 2018, Seoul, South Korea, October 22 - 26, 2018. New York, NY, Untied States: Association for Computing Machinery, Inc. doi: 10.1145/3240508.3240583

  • Qi, Xuewei, Luo, Yadan, Wu, Guoyuan, Boriboonsomsin, Kanok and Barth, Matthew J. (2017). Deep reinforcement learning-based vehicle energy efficiency autonomous learning system. IEEE Intelligent Vehicles Symposium, Redondo Beach, CA, United States, 11-14 June 2017. Piscataway, NJ, United States: IEEE. doi: 10.1109/ivs.2017.7995880

  • Yang, Yang, Luo, Yadan, Chen, Weilun, Shen, Fumin, Shao, Jie and Shen, Heng Tao (2016). Zero-shot hashing via transferring supervised knowledge. 24th ACM Multimedia Conference, MM 2016, Amsterdam, The Netherlands, 15 - 19 October 2016. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/2964284.2964319

Other Outputs

PhD and MPhil Supervision

Current Supervision

Completed Supervision