About me

Hi! My name is Yuchen Li. I am currently a senior researcher at Baidu Search Science, collaborating closely with Dr. Dawei Yin and Dr. Shuaiqiang Wang. I am also an adjunct researcher in Intelligent Network and Trusted Computing Laboratory at Shanghai Jiao Tong University, collaborating with Prof. Linghe Kong. I received my Ph.D. degree from the Department of Computer Science and Engineering at Shanghai Jiao Tong University in June 2024, under the supervision of Prof. Linghe Kong (Cheung Kong Scholar) and Prof. Guihai Chen (IEEE Fellow, NSFC Distinguished Young Scholar). From 2021 until my graduation, I served as a research intern in Big Data Laboratory at Baidu Inc., under the mentorship of Dr. Haoyi Xiong and Prof. Dejing Dou. I have published research papers in premium conferences and journals, and have been the recipient of three best paper awards or nominations, including ICDM, DSAA and PRICAI.
Research interests:
My research mainly focuses on data-driven intelligent computing for interconnected systems. Applications include information retrieval, large language models, AI for science, recommender systems, and mobile communication networks.
Prospective Interns:
I am looking for highly self-motivated research or applied interns (PhD or Master students) to join our Baidu Search Science team in Beijing! If you are interested in working with me in the area of information retrieval, data mining and large language models, please email liyuchen02 {at} baidu.com.

Publications

[Conference]

1. [ICDE'25] Yuchen Li, Hao Zhang, Yongqi Zhang, Xinyu Ma, Wenwen Ye, Naifei Song, Shuaiqiang Wang, Haoyi Xiong, Dawei Yin, Lei Chen.
   M2oERank: Multi-objective Mixture-of-Experts Enhanced Ranking for Satisfaction-oriented Web Search.
   The 41st IEEE International Conference on Data Engineering, 2025.
   
2. [KDD'25] Yuchen Li, Haoyi Xiong, Yongqi Zhang, Jiang Bian, Tianhao Peng, Xuhong Li, Shuaiqiang Wang, Linghe Kong, Dawei Yin.
   RankElectra: Semi-supervised Pre-training of Learning-to-Rank Electra for Web-scale Search.
   The 31st SIGKDD Conference on Knowledge Discovery and Data Mining, 2025.
   
3. [AAAI'25] Tianhao Peng, Xuhong Li, Haitao Yuan, Yuchen Li, Haoyi Xiong.
   SOLA-GCL: Subgraph-oriented Learnable Augmentation Method for Graph Contrastive Learning.
   The 39th Annual AAAI Conference on Artificial Intelligence, 2025.
   
4. [IJCAI'24] Yuchen Li, Haoyi Xiong, Linghe Kong, Shuaiqiang Wang, Zeyi Sun, Hongyang Chen, Guihai Chen, Dawei Yin.
   A Modular and Pre-trained Graphformer for Learning to Rank at Web-scale (Extended Abstract).
   The 33rd International Joint Conference on Artificial Intelligence, 2024.
   
5. [IJCAI'24] Yuchen Li, Haoyi Xiong, Linghe Kong, Jiang Bian, Shuaiqiang Wang, Guihai Chen, Dawei Yin.
   A Generative Pre-trained Learning to Rank Model with Over-parameterization for Web-Scale Search (Extended Abstract).
   The 33rd International Joint Conference on Artificial Intelligence, 2024.
   
6. [NeurIPS'24] Haizhou Du, Yijian Chen, Ryan Yang, Yuchen Li, Linghe Kong.
   HyperPrism: An Adaptive Non-linear Aggregation Framework for Distributed Machine Learning over Non-IID Data and Time-varying Communication Links.
   The 38th Conference on Neural Information Processing Systems, 2024.
   
7. [KDD'23] Yuchen Li, Haoyi Xiong, Linghe Kong, Qingzhong Wang, Shuaiqiang Wang, Guihai Chen, Dawei Yin.
   S2phere: Semi-Supervised Pre-training for Web Search over Heterogeneous Learning to Rank Data.
   The 29th SIGKDD Conference on Knowledge Discovery and Data Mining, 2023.
   
8. [ICDM'23] Yuchen Li, Haoyi Xiong, Linghe Kong, Zeyi Sun, Hongyang Chen, Shuaiqiang Wang, Dawei Yin.
   MPGraf: a Modular and Pre-trained Graphformer for Learning to Rank at Web-scale.
   The 23rd IEEE International Conference on Data Mining, 2023. (Acceptance Rate 9.37%) (Best Student Paper Award)
   
9. [ECML PKDD'23] Yuchen Li, Haoyi Xiong, Linghe Kong, Shuaiqiang Wang, Zeyi Sun, Hongyang Chen, Guihai Chen, Dawei Yin.
   LtrGCN: Large-Scale Graph Convolutional Networks-based Learning to Rank for Web Search.
   European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2023.
   
10. [DSAA'23] Yuchen Li, Haoyi Xiong, Linghe Kong, Jiang Bian, Shuaiqiang Wang, Guihai Chen, Dawei Yin.
    GS2P: A Generative Pre-trained Learning to Rank Model with Over-parameterization for Web-Scale Search.
    The 10th IEEE International Conference on Data Science and Advanced Analytics, 2023.
    
11. [ECML PKDD'22] Yuchen Li, Haoyi Xiong, Linghe Kong, Rui Zhang, Dejing Dou, Guihai Chen.
    Meta Hierarchical Reinforced Learning to Rank for Recommendation: A Comprehensive Study in MOOCs.
    European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2022.
    
12. [MOBICOM'21@Workshop] Junqin Huang, Linghe Kong, Jiejian Wu, Yutong Liu, Yuchen Li, Zhe Wang.
    Learning-based Congestion Control Simulator for Mobile Internet Education.
    MobiArch Workshop, 2021. (held with ACM MOBICOM)
    
13. [PRICAI'18] Chao Yu, Dongxu Wang, Tianpei Yang, Wenxuan Zhu, Yuchen Li, Hongwei Ge, Jiankang Ren.
    Adaptively Shaping Reinforcement Learning Agents via Human Reward.
    The 15th Pacific Rim International Conference on Artificial Intelligence, 2018. (Best Paper Nomination)
    

14. [TMC] Mingxin Cai, Chen Ma, Yuchen Li^†, Zhonghao Lyu, Yutong Liu, Linghe Kong^†, Guihai Chen.
    UCMM: Unsupervised Convolutional Networks for Accurate and Efficient Map Matching with Mobile Cellular Data.
    IEEE Transactions on Mobile Computing, 2025. （^†Corresponding author）
15. [TKDE] Tianhao Peng, Haitao Yuan, Yongqi Zhang, Yuchen Li, Peihong Dai, Qunbo Wang, Senzhang Wang, Wenjun Wu.
    TagRec: Temporal-Aware Graph Contrastive Learning with Theoretical Augmentation for Sequential Recommendation.
    IEEE Transactions on Knowledge and Data Engineering, 2025.
16. [MLJ] Yuchen Li, Haoyi Xiong, Linghe Kong, Jiang Bian, Shuaiqiang Wang, Guihai Chen, Dawei Yin.
    GS2P: A Generative Pre-trained Learning to Rank Model with Over-parameterization for Web-Scale Search.
    Machine Learning, 2024. (IEEE DSAA Best Paper Award - Journal Track)
17. [TSC] Haoyi Xiong, Bian Jiang, Yuchen Li^†, Xuhong Li, Mengnan Du, Shuaiqiang Wang, Dawei Yin, Sumi Helal.
    When Search Engine Services meet Large Language Models: Visions and Challenges.
    IEEE Transactions on Services Computing, 2024. （^†Corresponding author）
18. [NMI] Ning Wang, Jiang Bian, Yuchen Li, Xuhong Li, Shahid Mumtaz, Linghe Kong, Haoyi Xiong.
    Multi-purpose RNA Language Modeling with Motif-aware Pre-training and Type-guided Fine-tuning.
    Nature Machine Intelligence, 2024.
19. [TWC] Zhonghao Lyu, Yuchen Li, Guangxu Zhu, Jie Xu, H. Vincent Poor, Shuguang Cui.
    Rethinking Resource Management in Edge Learning: A Joint Pre-training and Fine-tuning Design Paradigm.
    IEEE Transactions on Wireless Communications, 2024.
20. [TKDE] Yuchen Li, Haoyi Xiong, Qingzhong Wang, Linghe Kong, Hao Liu, Haifang Li, Jiang Bian, Shuaiqiang Wang, Guihai Chen, Dejing Dou, Dawei Yin.
    COLTR: Semi-supervised Learning to Rank with Co-training and Over-parameterization for Web Search.
    IEEE Transactions on Knowledge and Data Engineering, 2023.
21. [TSC] Yuchen Li, Haoyi Xiong, Linghe Kong, Rui Zhang, Fangqin Xu, Guihai Chen, Minglu Li.
    MHRR: MOOCs Recommender Service with Meta Hierarchical Reinforced Ranking.
    IEEE Transactions on Services Computing, 2023.
22. [TKDD] Haoyi Xiong, Xiaofei Zhang, Jiamin Chen, Xinhao Sun, Yuchen Li, Zeyi Sun, Mengnan Du.
    Towards Explainable Artificial Intelligence (XAI): A Data Mining Perspective.
    ACM Transactions on Knowledge Discovery from Data. [Major Revison]
23. [TSC] Yuan Liao, Jiang Bian, Shilei Ji, Yuhui Yun, Shuo Wang, Yubo Zhang, Jiaming Chu, Tao Wang, Yuchen Li, Xuhong Li, Haoyi Xiong.
    SageCopilot: A LLM-empowered Autonomous Agent for Data Science as a Service.
    IEEE Transactions on Services Computing. [Under Review]
24. [NC] Tianhao Peng, Yuchen Li, Xuhong Li, Jiang Bian, Ning Sui, Shahid Mumtaz, Yanwu Xu, Linghe Kong, Haoyi Xiong.
    Pre-trained Molecular Language Models with Random Functional Group Masking.
    Nature Communications. [Under Review]