About Me

Keqiuyin Li (UTS-AAII)

I am current a Research Associate under Dist. Prof. Jie Lu’s ARC Laureate Project at Australian Artificial Intelligence Institute (AAII), University of Technology Sydney (UTS). I received my Ph.D degree in computer science from UTS in 2023. My research addresses transfer learning with multiple source domains. The primary objective of my research is to investigate the transformative potential of transfer learning in improving people’s lives, with a specific focus on enhancing data privacy protection to ensure secure data handling and unlock valuable insights. The contributions of my works addressed three questions in machine learning and artificial intelligence: data scarcity, data privacy and knowledge extraction.

I am available to supervise PhD and Master Candidates by Research with backgrounds in transfer learning, cross-modality learning, fuzzy systems and image super-resolution.

Research Interests

Machine Learning, Unsupervised Learning, Transfer Learning, Computer Vision, Image Super-Resolution

News and Updates

[News] [Submit you FUZZ IEEE papers]
[News] Submit you IJCNN papers
We are organising special sessions in FUZZ-IEEE SS, Reims, France, June 30 - July 5 2025.
FUZZ-IEEE 2025 Special Session-Fuzzy Machine Learning- Call for Papers
We are organising special sessions in IJCNN SS, Rome, Italy, July 6 - July 9 2025.
IJCNN 2025 Special Session-Domain Adaptation for Complex Situations- Call for Papers
WCCI FUZZ-IEEE 2024 Special Session-Fuzzy Machine Learning- Call for Papers
WCCI IJCNN 2024 Special Session-Domain Adaptation for Complex Situations- Call for Papers
Aug 2023：FUZZ-IEEE, Songdo Incheon, Korea.
June 2023：IJCNN, Gold Coast, Australia.

Latest Research

Journal

Federated Fuzzy Transfer Learning with Domain and Category Shifts, IEEE Transactions on Fuzzy System, 2024. Paper Code
Multi-Source Domain Adaptation Handling Inaccurate Label Spaces, Neurocomputing, 2024. Paper
Source-Free Unsupervised Domain Adaptation: Current Research and Future Directions, Neurocomputing, 2023. Paper
Source-free multi-domain adaptation with fuzzy rule-based deep neural networks, IEEE Transactions on Fuzzy System, 2023. Paper Code
Multidomain adaptation with sample and source distillation, IEEE Transactions on Cybernetics, 2023. Paper Code

Conference

Multi-Source Domain Adaptation with Incomplete Source Label Spaces, in Proceedings of International Conference on Knowledge-Based and Intelligent Information and Engineering Systems (KES) 2023.
Attention-Bridging TS Fuzzy Rules for Universal Multi-Domain Adaptation without Source Data, in Proceedings of the IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2023. Paper
Source-free multi-domain adaptation with generally auxiliary model training, in Proceedings of the International Joint Conference on Neural Networks (IJCNN), Italy, July 18-23, 2022. Paper Code

Awards

2023: ISKE Best Paper Award
2023: FUZZ-IEEE Best Paper Award
2022: UTS HDR Excellence Awards
2022：AAII Student Best Paper Award
2021: UTS-FEIT Showcase TOP-3 Winner

Services

Chair/Organiser:

2024 FUZZ-IEEE SS: Fuzzy machine learning
2024 IJCNN SS: : Domain adaptation for complex situations: Theories, Algorithms and Applications
2023 FUZZ-IEEE SS: Fuzzy machine learning

PC Member:

WCCI 2024.
AJCAI 2023.

Journal reviewer:

TKDE, TNNLS, TCYB, TFS, TCSVT, IEEE/CAA, Knowledge-Based Systems, Neurocomputing.