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
2017
Journal Article
Robust discrete code modeling for supervised hashing
Luo, Yadan, Yang, Yang, Shen, Fumin, Huang, Zi, Zhou, Pan and Shen, Heng Tao (2017). Robust discrete code modeling for supervised hashing. Pattern Recognition, 75, 128-135. doi: 10.1016/j.patcog.2017.02.034
2017
Conference Publication
Deep reinforcement learning-based vehicle energy efficiency autonomous learning system
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
2016
Conference Publication
Zero-shot hashing via transferring supervised knowledge
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
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
Towards Open-vocabulary 3D Object Detection
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
Data-Centric Advancements in Neural Radiance Fields for 3D Reconstruction
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
Maximizing Object Detection Dataset Efficiency through the Power of Active Learning
Principal Advisor
Other advisors: Professor Helen Huang
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Doctor Philosophy
Controlling Knowledge Dynamics in Pre-trained Deep Neural Networks
Associate Advisor
Other advisors: Professor Helen Huang, Associate Professor Mahsa Baktashmotlagh
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Doctor Philosophy
Adaptive Human-Robot Interaction for Unstructured, Dynamic Environments with Rich Physical Interactions
Associate Advisor
Other advisors: Associate Professor Jen Jen Chung
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Doctor Philosophy
Advancing Embodied Visual Content understanding through Egocentric Videos
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
Foundation-Model-Guided Gaussian Modelling for Immersive 3D Scene Simulation
Associate Advisor
Other advisors: Professor Helen Huang
Completed supervision
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2026
Doctor Philosophy
Towards Generalizable 3D Vision Learning under Real-World Constraints
Principal Advisor
Other advisors: Professor Helen Huang, Associate Professor Mahsa Baktashmotlagh
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2025
Doctor Philosophy
Developing Efficient and Stable Perovskite Quantum Dot Light Emitting Diodes
Associate Advisor
Other advisors: Professor Lianzhou Wang
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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
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