About me

Hi! My name is Yuchen Li. I am now a senior researcher at Baidu Search Science. 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 and Prof. Guihai Chen. From 2021 until my graduation, I served as a visiting researcher in Big Data Laboratory at Baidu Inc., under the mentorship of Dr. Haoyi Xiong and Prof. Dejing Dou, and collaborated closely with Dr. Shuaiqiang Wang and Dr. Dawei Yin.
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.

Publications

[Journal]

1. [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)
2. [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.
3. [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）
4. [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.
5. [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.
6. [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.
7. [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]
8. [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. [Major Revison]
9. [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. [Under Review]
10. [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]
11. [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]

12. [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.
    
13. [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.
    
14. [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.
    
15. [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.
    
16. [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.
    
17. [ICDM'23] Yuchen Li, Haoyi Xiong, Linghe Kong, Shuaiqiang Wang, Zeyi Sun, Hongyang Chen, Guihai Chen, 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)
    
18. [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.
    
19. [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.
    
20. [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.
    
21. [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)
    
22. [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)