Peijie Sun (孙培杰)

Peijie Sun (孙培杰)

Nanjing University of Posts and Telecommunications

I joined the School of Computer Science, Nanjing University of Posts and Telecommunications (NJUPT) since October 2024. I am now working on recommendation algorithms, user modeling, social network modeling, and LLM-based recommendation research. If you are seeking any form of academic cooperation, please feel free to email me at sun.hfut@gmail.com.

I completed my postdoctoral researcher job from July 2022 to September 2024 at the Department of Computer Science and Technology, Tsinghua University, in Beijing, China, under the supervision of Professor Min Zhang (张敏).

I obtained my bachelor’s, master’s, and doctoral degrees from the School of Computer Science and Information Engineering, Hefei University of Technology. During my master’s and doctoral studies, I was guided by Meng Wang Meng Wang (汪萌) and Le Wu (吴乐).

During my doctoral studies, I visited Missouri University of Science and Technology, Rolla Campus, from December 2018 to July 2019, where I received guidance from Professor Yanjie Fu (傅衍杰). Additionally, I visited the Social Computing Group at Microsoft Research Asia from May 2021 to July 2021, under the supervision of Professor Fangzhao Wu (吴方照).

My research interests include recommendation algorithms, user modeling, social network modeling, and LLM-based recommendation research. I have published 20+ papers at the top international AI conferences such as WWW, KDD, SIGIR, and AI Journals such as IEEE TKDE, IEEE TMM, and ACM TOIS.

🎉 My WWW 2024 Industry Track work achieved a 50.65% increase in online revenue on Huawei HiMedia, and an 18.43% uplift in traffic across Huawei-related business scenarios.

My CV can be downloaded via this link. The Chinese Version can be downloaded via another link.

🔥 News

  • 2024.09: 🎉 One long paper is accepted by EMNLP 2024.
  • 2024.08: 🎉 One paper is accepted by TOIS 2024.
  • 2024.07: 🎉 Two long papers are accepted by RecSys 2024 Reproducibility Track
  • 2024.07: 🎉 One long paper is accepted by RecSys 2024
  • 2024.05: 🎉 Two long papers are accepted by KDD 2024
  • 2024.03: 🎉 Two long papers are accepted by SIGIR 2024, and one resource paper is accepted by SIGIR 2024
  • 2024.03: 🎉 One long paper is accepted by DASFAA 2024, and one short paper is accepted by DASFAA 2024
  • 2024.02: 🎉 One long paper is accepted by WWW 2024 Industry Track
  • 2024.01: 🎉 One long paper is accepted by WWW 2024 Research Track
  • 2023.10: 🎉 One paper is accepted by IEEE TKDE
  • 2023.08: 🎉 One paper is accepted by CIKM 2023
  • 2023.05: 🎉 One paper is accepted by KDD 2023
  • 2023.04: 🎉 Two papers are accepted by SIGIR 2023
  • 2023.01: I join the Department of Computer Science and Technology, Tsinghua University as a postdoc in China!

📝 Publications

SIGIR 2024
sym

Sequential Recommendation with Latent Relations based on Large Language Model
Shenghao Yang, Weizhi Ma, Peijie Sun, Qingyao Ai, et al.

  • Academic Impact: In this work, we leverage rich world knowledge which is compressed in LLM to discover latent item relations for enhanced recommendation.
WWW 2024 Industry
sym

Collaborative-Enhanced Prediction of Spending on Newly Downloaded Mobile Games under Consumption Uncertainty
Peijie Sun, Yifan Wang, Min Zhang, Chuhan Wu, et al.

  • Indudtry Impact: The research outcomes of this work achieved a 50.65% increase in online revenue on Huawei HiMedia, and an 18.43% uplift in traffic across Huawei-related business scenarios.
IEEE TKDE 2023
sym

Neighborhood-Enhanced Supervised Contrastive Learning for Collaborative Filtering
Peijie Sun, Le Wu, Kun Zhang, Xiangzhi Chen, Meng Wang.

PaperWithCode
Code

  • Academic Impact: Our proposed algorithm outperforms the best algorithm on the candidate matching leaderboard on BARS, significantly on Yelp and Gowalla datasets. Our proposed nearest neighbor-enhanced supervised contrastive module significantly outperforms the baseline model. On three real-world datasets, Yelp2018, Gowalla, and Amazon-Book, our model surpasses the original SGL by 10.09%, 7.09%, and 35.36% on NDCG@20, respectively.
CIKM 2023
sym

Understanding User Immersion in Online Short Video Interaction
Zhiyu He, Shaorun Zhang, Peijie Sun, Jiayu Li, Xiaohui Xie, Min Zhang, Yiqun Liu

  • Academic Impact: In this study, we primarily investigate users’ immersion states while browsing short videos. We argue that, instead of traditional metrics like user dwell time on short videos, immersion state should be considered as a more effective evaluation criterion for user satisfaction with short video content.
SIGIR 2019
sym

A Neural Influence Diffusion Model for Social Recommendation
Le Wu, Peijie Sun, Yanjie Fu, Richang Hong, Xiting Wang, Meng Wang

  • Academic Impact: We are among the first to apply graph convolutional techniques to social recommendation tasks. According to Google Scholar, as of today, our work has garnered over 500 citations. Besides, we have also provied the tensorflow and paddlepaddle version code.

  1. EMNLP 2024 A User-Centric Benchmark for Evaluating Large Language Models, Jiayin Wang, Fengran Mo, Weizhi Ma, Peijie Sun, Min Zhang, Jian-Yun Nie.

  2. TOIS 2024 Feature-Enhanced Neural Collaborative Reasoning for Explainable Recommendation, Xiaoyu Zhang, Shaoyun Shi, Yishan Li, Weizhi Ma, Peijie Sun, et al.

  3. KDD 2024 Long Popularity-Aware Alignment and Contrastive for Mitigating Popularity Bias, Miaomiao Cai, Lei Chen, Yifan Wang, Haoyue Bai, Peijie Sun, et al.

  4. KDD 2024 Long Double Correction Framework for Denoising Recommendation, Zhuangzhuang He, Yifan Wang, Yonghui Yang, Peijie Sun, et al.

  5. SIGIR 2024 Resource EEG-SVRec: An EEG Dataset with User Multidimensional Affective Engagement Labels in Short Video Recommendation, Shaorun Zhang, Zhiyu He, Ziyi Ye, Peijie Sun, et al.

  6. SIGIR 2024 Long Aiming at the Target: Filter Collaborative Information for Cross-Domain Recommendation, Hanyu Li, Weizhi Ma, Peijie Sun, Jiayu Li, et al.

  7. DASFAA 2024 Long A Situation-aware Enhancer for Personalized Recommendation, Jiayu Li, Peijie Sun, Chumeng Jiang, Weizhi Ma, Qingyao Ai, Min Zhang.

  8. DASFAA 2024 Short Common Sense Enhanced Knowledge-based Recommendation with Large Language Model, Shenghao Yang, Weizhi Ma, Peijie Sun, Min Zhang, et al.

  9. WWW 2024 Long Intersectional Two-sided Fairness in Recommendation, Yifan Wang, Peijie Sun, Weizhi Ma, Min Zhang, et al.

  10. KDD 2023 Long Unbiased Delayed Feedback Label Correction for Conversion Rate Prediction, Yifan Wang, Peijie Sun, Min Zhang, Qinglin Jia, et al.

  11. SIGIR 2023 Long Topic-enhanced Graph Neural Networks for Extraction-based Explainable Recommendation, Jie Shuai, Le Wu, Kun Zhang, Peijie Sun, et al.

  12. SIGIR 2023 Long Intent-aware Ranking Ensemble for Personalized Recommendation, Jiayu Li, Peijie Sun, Zhefan Wang, Weizhi Ma, et al.

  13. IEEE TMM 2023 Multimodal graph contrastive learning for multimedia-based recommendation, Kang Liu, Feng Xue, Dan Guo, Peijie Sun, et al.

  14. SIGIR 2022 Long ProFairRec: Provider fairness-aware news recommendation, Tao Qi, Fangzhao Wu, Chuhan Wu, Peijie Sun, et al.

  15. SIGIR 2022 Long A review-aware graph contrastive learning framework for recommendation, Jie Shuai, Kun Zhang, Le Wu, Peijie Sun, et al.

  16. ACM TOIS 2021 An unsupervised aspect-aware recommendation model with explanation text generation, Peijie Sun, Le Wu, Kun Zhang, Yu Su, et al.

  17. IEEE TKDE 2020 Diffnet++: A neural influence and interest diffusion network for social recommendation, Le Wu, Junwei Li, Peijie Sun, Richang Hong, et al.

  18. WWW 2020 Long Dual learning for explainable recommendation: Towards unifying user preference prediction and review generation, Peijie Sun, Le Wu, Kun Zhang, Yanjie Fu, et al.

  19. SIGIR 2019 Long A neural influence diffusion model for social recommendation, Le Wu, Peijie Sun, Yanjie Fu, Richang Hong, et al.

  20. IEEE Trans. SMC 2018 Collaborative neural social recommendation, Le Wu, Peijie Sun, Richang Hong, Yong Ge, et al.

  21. SIGIR 2018 Long Attentive recurrent social recommendation, Peijie Sun, Le Wu, Meng Wang.

🎖 Fellowships and Awards

  • 2022.07-2024.08 China Postdoctoral Science Foundation Special Funding for the 4th Batch (Pre-Station)
  • 2024.04 Excellent doctoral dissertation of Anhui Province (Top 1%)
  • 2020.12 National Scholarship for Doctoral Students in China (Undergraduate) (Top 1%)
  • 2019.07 SIGIR2019 Travel Grant
  • 2018.07 SIGIR2018 Volunteer Travel Grant

📖 Educations

  • 2018.07 - 2022.05, PhD, Signal and Information Processing, School of Computer Science and Information Engineering, Hefei University of Technology, Hefei, China. Advised by Meng Wang and Le Wu
  • 2015.09 - 2018.07, Master, Signal and Information Processing, School of Computer Science and Information Engineering, Hefei University of Technology, Hefei, China. Advised by Meng Wang and Le Wu
  • 2011.09 - 2015.07, Undergraduate, Electronic Information Science and Technology, Hefei University of Technology, Hefei, China.

💻 Working Experience & Internships