Yonghui Yang

Yonghui Yang

Hefei University of Technology (HFUT)

🎓About Me

I am a last-year Ph.D student at Hefei University of Technology(HFUT), and supervised by Prof. Le Wu and Prof. Richang Hong. My research interests include Data-centric Recommendation, Robust Graph Learning, and LLM safety. I have published several papers in leading journals and conferences, such as IEEE TKDE, IEEE TBD, KDD, SIGIR, ACM Multimedia, and IJCAI.

📍 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_1-22: 🎉🎉 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

  • 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 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

  • 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