Yangjian Wu

M.S. Student in Control Engineering, Xiamen University

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Email: wuyangjian@stu.xmu.edu.cn

Xiamen, Fujian, China

I am a Master’s student in Control Engineering at Xiamen University, advised by Prof. Qifeng Zhou. My research interests include large language models (LLMs), multi-agent debate (MAD), event causality identification (ECI), and graph neural networks (GNNs).

Research Interests

  • Large Language Models (LLMs)
  • Multi-Agent Debate (MAD)
  • Event Causality Identification (ECI)
  • Graph Neural Networks (GNN)

Education

  • M.S. in Control Engineering, School of Aerospace Engineering, Xiamen University, 2025 – present (expected 2028). Advisor: Prof. Qifeng Zhou.
  • B.S. in Automation, School of Mechanical and Electrical Engineering, Hainan University, 2021 – 2025. Advisor: Prof. Xiaofeng Xie.

Internship Experience

  • 2022 – 2023 Research Intern, Business Artificial Intelligence Lab, Nanyang Technological University (supervised by Prof. Teik Toe Teoh). Developed WavBriVL, a diffusion-based framework for cross-modal audio–visual representation learning and generation. I constructed a 20,000-pair audio–image dataset through web crawling and preprocessing pipelines, implemented a VQGAN-based generative framework, and achieved 91.17% audio classification accuracy, outperforming the then state-of-the-art Wav2CLIP by 5.22%. The work resulted in two publications at ICONIP 2023 and MRL 2023.

selected publications

  1. CAC
    CSCGCL: A New Seed-enhanced Community Detection Approach with Graph Contrastive Learning
    Debo Zhao, Qifeng Zhou, and Yangjian Wu
    In 2025 China Automation Congress (CAC), 2025
    DOI Bib
  2. MRL
    UniBriVL: Robust Audio Representation and Generation of Audio Driven Diffusion Models
    Sen Fang, Bowen Gao, Yangjian Wu, and Teik Toe Teoh
    In Proceedings of the 3rd Workshop on Multi-lingual Representation Learning (MRL), 2023
    DOI Bib
  3. ICONIP
    Exploring Efficient-Tuned Learning Audio Representation Method from BriVL
    Sen Fang, Yangjian Wu, Bowen Gao, Jingwen Cai, and Teik Toe Teoh
    In Proceedings of the 30th International Conference on Neural Information Processing (ICONIP 2023), Communications in Computer and Information Science, 2023
    DOI Bib