[1]. The First Prize for Chongqing Science and Technology Progress Award in 2020;

[2]. Best Paper Nomination Award of CCF BigData’2020;

[3]. Best Paper Nomination Award of ICNSC’16;

[1].Xiaoyu Shi, Quanliang Liu, Hong Xie, Di Wu, Bo Peng, Mingsheng Shang Defu Lian, Relieving Popularity Bias in Interactive Recommendation: A Diversity-Novelty-Aware Reinforcement Learning Approach, Vol. 42, No. 2, ACM Transactions on Information Systems (TOIS), (CCF-A类期刊, 中科院二区, IF 5.6);

[2]. Xiaoyu Shi, Quanling Liu and Mingsheng Shang. Towards Long-term Fairness in Interactive Recommendation: A Maximum Entropy Reinforcement Learning Approach. IEEE International Conference on Web Services (ICWS 2023). (CCF-B类会议);

[3].Bingchao Wang, Xiaoyu Shi*, and Mingsheng Shang. A Self-decoupled Interpretable Prediction Framework for Highly-Variable Cloud Workloads. in International Conference on Database Systems for Advanced Applications (DASFAA), 2023, pp. 588–603. (CCF-B类会议);

[4] Zihui Zhao, Xiaoyu Shi*, and Mingsheng Shang. Performance and cost-aware task scheduling via deep reinforcement learning in cloud environment. in International Conference on Service-Oriented Computing, 2022, pp. 600–615. (CCF- B类会议);

[5] Xiaoyu Shi, Qiang He, Xin Luo, Yanan Bai, and Mingsheng Shang. Large-scale and scalable latent factor analysis via distributed alternative stochastic gradient descent for recommender systems. IEEE Transactions on Big Data vol. 8, no. 2, p. 420–431, 2022. (CCF-C,中科院二区, IF: 7.031)

[6]Qingxian Wang, Suqiang Wu, Yanan Bai, Quanliang Liu, and Xiaoyu Shi*. Neighbor Importance-aware Graph Collaborative Filtering for Item Recommendation. Neurocomputing, p. 126429, 2023, (CCF-C,中科院二区, IF:6) ;

[7] Xiaoyu Shi, Quanliang Liu, Yanan Bai, and Mingsheng Shang. RTiSR: a review-driven time interval-aware sequential recommendation method. Journal of Big Data, vol. 10, no. 1, p. 32, 2023. (中科院二区, IF:7.914);

[8] Tianqi Shang, Xinxin Li, Xiaoyu Shi*, and Qingxian Wang. Joint Modeling Dynamic Preferences of Users and Items Using Reviews for Sequential Recommendation. In Pacific-Asia Conference on Knowledge Discovery and Data Mining(PAKDD), 2021, pp. 524–536. (CCF推荐C类会议)

[9]. Hong Xie, Mingze Zhong, Xiaoyu Shi, Xiaoying Zhang, Jiang Zhong, Mingsheng Shang. Probabilistic Modeling of Assimilate-Contrast Effects in Online Rating Systems. IEEE Transactions on Knowledge and Data Engineering, DOI: 10.1109/TKDE.2023.3292352. (CCF-A类期刊, 中科院二区, IF 8.412);

[10] Xiaoyu Xu, Xiaoyu Shi, and Mingsheng Shang. Graph neural networks via contrast between separation and aggregation for self and neighborhood. Expert Systems with Applications, vol. 224, p. 119994, 2023. (CCF-C类期刊, 中科院一区, IF 8.412).