Huafei Huang

Huafei Huang

About Me

Huafei Huang is currently a PhD student at STEM, University of South Australia (UniSA). Before that, he received a BSc. degree in Internet of Things Engineering from North University of China (NUC), in 2020, and the MSc degree in Software Engineering from Dalian University of Technology (DUT), in 2023. He received 138 citations to his works.

Experiences

  • North University of China (NUC)
    B.Sc. (School of BigData), 2016-2020
  • Dalian University of Technology (DUT)
    M.Sc. (School of Software), 2020-2023
  • University of South Australia (UniSA)
    Ph.D. Student (STEM), 2024-current

Research Interests

  • Data Mining, Anomaly Detection, Knowledge Graphs, Fairness AI
  • Graph Learning, Large Language Models, Medical AI

Honors and Awards

  • Most Popular Article Award, CAAI National Conference on Big Data & Social Computing (BDSC2023)
  • Outstanding Graduate of the College, North University of China (2020)
  • The Second-class All-rounder Scholarship (2019,2020)
  • National Encouragement Scholarship (Sponsored by the Ministry of Education) (2018,2019)
  • The First-class All-rounder Scholarship (2017,2018)

Invited Reviewer

  • Conferences: AAAI, KDD, WWW/TheWebConf, etc.
  • Journals: TNNLS, TITS, ESWA, EAAI, TIST, IJCS, HSSCOMMS, Neurocomputing, Frontiers in Big Data, Heliyon, etc.

Preprints

  • Renqiang Luo, Ziqi Xu, Xikun Zhang, Qing Qing, Huafei Huang, Enyan Dai, Zhe Wang, and Bo Yang. 2025. Fairness in Graph Learning Augmented with Machine Learning: A Survey. arXiv arXiv preprint arXiv: 2504.21296, DOI: 10.48550/arXiv.2504.21296. (PDF)

Publications

  • Shoulin Yin, Liguo Wang, Tao Chen, Huafei Huang, Jing Gao, Jianing Zhang, Meng Liu, Peng Li, and Chengpei Xu. 2025. LKAFormer: A Lightweight Kolmogorov-Arnold Transformer Model for Image Semantic Segmentation. ACM Transactions on Intelligent Systems and Technology., DOI: 10.1145/3759254. (PDF)
  • Ciyuan Peng, Huafei Huang, Tianqi Guo, Chengxuan Meng, Jingjing Zhou, Wenhong Zhao, Ruwan Tennakoon, and Feng Xia. 2025. Joint Structural-Functional Brain Graph Transformer. ACM Transactions on Intelligent Systems and Technology. 16(3): 1-15, DOI: 10.1145/3729243. (PDF)
  • Shuo Yu, Zhuoyang Han, Feng Ding, Huafei Huang, Renqiang Luo, Guoqing Han, and Feng Xia. 2025. Multi-type Social Patterns-based Graph Learning. Neurocomputing. 637: 130039, DOI: 10.1016/j.neucom.2025.130039. (PDF)
  • Renqiang Luo, Huafei Huang, Ivan Lee, Chengpei Xu, Jianzhong Qi, and Feng Xia. 2025. FairGP: A Scalable and Fair Graph Transformer Using Graph Partitioning. Proceedings of the AAAI Conference on Artificial Intelligence (AAAI). 12319-12327, DOI: 10.1609/aaai.v39i12.33342 (PDF) (CODE)
  • Renqiang Luo, Huafei Huang, Shuo Yu, Zhuoyang Han, Jiayuan He, Xiuzhen Zhang, and Feng Xia. 2024. FUGNN: Harmonizing Fairness and Utility in Graph Neural Networks Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD). 2072-2081, DOI: 10.1145/3637528.3671834. (PDF) (CODE)
  • Renqiang Luo, Huafei Huang, Shuo Yu, Xiuzhen Zhang, and Feng Xia. 2024. FairGT: A Fairness-aware Graph Transformer. Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI). 449-457, DOI: 10.24963/ijcai.2024/50 (PDF) (CODE)
  • Huafei Huang, Xu Yuan, Shuo Yu, Wenhong Zhao, Osama Alfarraj, Amr Tolba, and Feng Xia. 2024. Few-shot Semantic Segmentation for Consumer Electronics: An Inter-class Relation Mining Approach. IEEE Transactions on Consumer Electronics. 70(1): 3709-3721, DOI: 10.1109/TCE.2024.3373630. (PDF) (CODE)
  • Shuo Yu, Huafei Huang, Yanming Shen, Pengfei Wang, Qiang Zhang, Ke Sun, Honglong Chen. 2024. Formulating and Representing Multi-agent Systems with Hypergraphs. IEEE Transactions on Neural Networks and Learning Systems. 36(3):4599-4613, DOI: 10.1109/TNNLS.2024.3368111. (PDF) (CODE)
  • Huafei Huang, Feng Ding, Fengyi Zhang, Yingbo Wang, Ciyuan Peng, Ahsan Shehzad, Qihang Lei, Lili Cong, and Shuo Yu. 2023. Knowledge Graph Completion via Subgraph Topology Augmentation. In Chinese National Conference on Social Media Processing (SMP). 14-29, DOI: 10.1007/978-981-99-7596-9_2. (PDF)
  • Tingting Wang, Feng Ding, Naiwen Luo, Qihang Lei, Huafei Huang, Tong Zhang, and Shuo Yu. 2023. MDC: An Interpretable GNNs Method Based on Node Motif Degree and Graph Diffusion Convolution. In China National Conference on Big Data and Social Computing (BDSC). (Most Popular Article Award) 362–374, DOI: 10.1007/978-981-99-3925-1_24. (PDF)
  • Xu Yuan, Ying Yang, Huafei Huang, Shuo Yu, and Lili Cong. 2022. Mining Implicit Relations Among Image Channels for Few-Shot Semantic Segmentation. In 2022 IEEE International Conference on Ubiquitous Intelligence and Computing (UIC). 275-284, DOI: 10.1109/SmartWorld-UIC-ATC-ScalCom-DigitalTwin-PriComp-Metaverse56740.2022.00062. (PDF)
  • Shuo Yu, Huafei Huang, Minh N. Dao, and Feng Xia. 2022. Graph Augmentation Learning. 2022. In Companion Proceedings of the Web Conference 2022 (WWW workshop). 1063–1072. DOI: 10.1145/3487553.3524718 (PDF) (CODE)
  • Xu Yuan, Na Zhou, Shuo Yu, Huafei Huang, Zhikui Chen, and Feng Xia. 2021. Higher-order Structure Based Anomaly Detection on Attributed Networks. In 2021 IEEE International Conference on Big Data (IEEE BigData). 2691–2700. DOI: 10.1109/BigData52589.2021.9671990. (PDF) (CODE)