Yonghui Yang

Yonghui Yang

Hefei University of Technology (HFUT)

🎓About Me

I am a Research Fellow at the National University of Singapore, working with Prof. Tat-Seng Chua. I obtained my Ph.D from the Hefei University of Technology(HFUT), and supervised by Prof. Le Wu and Prof. Richang Hong. My research interests include data-centric recommendation(e.g., graph recommendation, LLM-based recommendation, and so on) and LLM safety(especially LLM alignment and reasoning safety). I have published several papers in leading journals and conferences, such as IEEE TKDE, IEEE TBD, KDD, SIGIR, ACM Multimedia, and IJCAI. If you are seeking any form of academic cooperation, please feel free to email me at yyh.hfut@gmail.com.

📍 Contact

  • Key Laboratory of Knowledge Engineering with Big Data
  • School of Computer Science and Information Engineering, School of Artificial Intelligence Hefei University of Technology (HFUT).
  • Office: Room 801, Kejiao A Building, Feicui Campus of HFUT, Hefei, Anhui, China, 230601
  • Email: yyh.hfut@gmail.com
  • Wechat: 15755107343
  • Google Scholar

🔥 News

2025_04_05: 🎉🎉 Two papers on Robust Recommendation are accepted by SIGIR’25.

2025_01-22: 🎉🎉 One paper on Denoising-based Multimodal Recommendation is released on ArXiv.

2024_11-26: 🎉🎉 One paper on Cross-Domain Recommendation is accepted by IEEE TKDE.

2024_11-16: 🎉🎉 One paper on Graph-based Cognitive Diagnosis is accepted by KDD’25.

2024-05-18：🎉🎉 Two papers on Recommendation Denoising are accepted by KDD’24.

2024_04-17: 🎉🎉 One paper on Fairness-aware Recommendation is accepted by IJCAI’24.

2023_12-7: 🎉🎉 One paper on Hyperbolic Social Recommendation is accepted by IEEE TKDE.

2023_11-27: 🎉🎉 One paper on Cold-start Recommendation is accepted by IEEE TBD.

2023_7-26: 🎉🎉 One paper on Cold-start Recommendation is accepted by MM’23.

2023_4-5: 🎉🎉 One paper on Self-supervised Graph Recommendation is accepted by SIGIR’23.

💻 Selected Research Papers

† co-first author, * corresponding author

My full paper list can also be found at Google Scholar.

Representative Papers

Preprint Papers

  • ArXiv 2025 Yonghui Yang, Le Wu, Zhuangzhuang He, Zhengwei Wu, Richang Hong, Meng Wang. Less is More: Information Bottleneck Denoised Multimedia Recommendation. [Paper]

In the year of 2025:

  • SIGIR 2025 Yonghui Yang, Le Wu, Yuxin Liao, Zhuangzhuang He, Pengyang shao, Richang Hong, Meng Wang. Invariance Matters: Empowering Social Recommendation via Graph Invariant Learning. [Paper] [Code]
  • SIGIR 2025 Yuxin Liao, Yonghui Yang, Min Hou, Le Wu, Hefei Xu, Hao Liu. Mitigating Distribution Shifts in Sequential Recommendation: An Invariance Perspective.

In the year of 2024:

  • IEEE TKDE Zihan Wang, Yonghui Yang *, Le Wu *, Richang Hong, Meng Wang. Making Non-overlapping Matters: An Unsupervised Alignment enhanced Cross-Domain Cold-Start Recommendation.[Paper] [Code]

  • KDD 2025 Pengyang Shao†, Yonghui Yang†, Chen Gao, Lei Chen, Kun Zhang, Chenyi Zhuang, Le Wu, Meng Wang. Exploring Heterogeneity and Uncertainty for Graph-based Cognitive Diagnosis Models in Intelligent Education. [Paper] [Code]

  • KDD 2024 Yonghui Yang, Le Wu, Zihan Wang, Zhuangzhuang He, Richang Hong, Meng Wang. Graph Bottlenecked Social Recommendation. [Paper] [Code]

  • IJCAI 2024 Junsong Xie†, Yonghui Yang†, Zihan Wang, Le Wu. Learning Fair Representations for Recommendation via Information Bottleneck Principle. [Paper] [Code]

In the year of 2023:

  • IEEE TKDE Yonghui Yang, Le Wu, Kun Zhang, Richang Hong, Hailin Zhou, Zhiqiang Zhang, Jun Zhou, Meng Wang. Hyperbolic Graph Learning for Social Recommendation. [Paper] [Code]

  • SIGIR 2023 Yonghui Yang, Zhengwei Wu, Le Wu, Kun Zhang, Richang Hong, Zhiqiang Zhang, Jun Zhou, Meng Wang. Generative-Contrastive Graph Learning for Recommendation. [Paper] [Code]

In the year of 2021:

  • SIGIR 2021 Yonghui Yang, Le Wu, Richang Hong, Kun Zhang, Meng Wang. Enhanced Graph Learning for Collaborative Filtering via Mutual Information Maximization. [Paper] [Code]

In the year of 2021:

  • SIGIR 2020 Le Wu, Yonghui Yang, Kun Zhang, Richang Hong, Yanjie Fu, Meng Wang. Joint Item Recommendation and Attribute Inference: An Adaptive Graph Convolutional Network Approach. [Paper] [Code]

  • SIGIR 2020 Le Wu, Yonghui Yang, Lei Chen, Richang Hong, Meng Wang. Learning to Transfer Graph Embeddings for Inductive Graph based Recommendation. [Paper]

🥇 Honors and Awards

  • 2025.04 Best Papre Reward at TIME 2025(Workshop on TheWebConf 2025)
  • 2024.12 National Scholarship
  • 2023.05 SIGIR 2023 Student Travel Grant
  • 2022.12 Excellent Master’s Thesis in Anhui Province
  • 2021.08 National First Prize in China Collegiate Computing Contest 2021-Big Data Challenge
  • 2020.12 National Scholarship
  • 2020.05 SIGIR 2020 Student Travel Grant