Mingyue Cheng (程明月)  

Ph.D, Associate Reseacher

State Key Laboratory of Cognitive Intelligence
School of Computer Science and Technology,    School of Data Science
University of Science and Technology of China (USTC)

Email: mycheng@ustc.edu.cn  
Add: 706, East Lab Building of Science and Technology, West Campus of USTC, Hefei, Anhui, China, 230027

Biography

I am an Associate Reseacher at the School of Computer Science and Technology and School of Data Science, University of Science and Technology of China (USTC) and State Key Laboratory of Cognitive Intelligence. I obtained my Ph.D. degree advised by Prof. Qi Liu at Anhui Province Key Laboratory of Big Data Analysis and Application .

Research Interests

My primary research interests involve data mining and machine learning algorithms from temporal and sequenced data for applications in life science and healthcare. I am passionate about building powerful (effective and efficient) and trustworthy (privacy-ware and explainable) AI. Secifically, I am interested in the following topics:


**欢迎有志于人工智能方向的脚踏实地而又积极主动的本科生、研究生同学加入实验室，与我一同发掘时序数据中的隐藏的知识，也欢迎大家使用我们精心打造的文修智能助写平台进行写作效率与技能提升**

Working Experiences

Education

Selected Publications (Google Scholar) (Github)

(* Corresponding Author, + Equal Contribution)

  1. Mingyue Cheng, Jiqian Yang, Tingyue Pan, Qi Liu*, Zhi Li, ConvTimeNet: A Deep Hierarchical Fully Convolutional Model for Multivariate Time Series Analysis. (Preprint) [PDF]
  2. Mingyue Cheng, Yiheng Chen, Qi Liu*, Zhiding Liu, Yucong Luo, Advancing Time Series Classification with Multimodal Language Modeling. (Preprint) [PDF] [CODE]
  3. Mingyue Cheng, Xiaoyu Tao, Qi Liu*, Hao Zhang, Yiheng Chen, Chenyi Lei, Learning Transferable Time Series Classifier with Cross-Domain Pre-training from Language Model. (Preprint) [PDF] [CODE]
  4. Mingyue Cheng, Qi Liu*, Zhiding Liu, Hao Zhang, Rujiao Zhang, Enhong Chen, TimeMAE: Self-supervised Representation of Time Series with Decoupled Masked Autoencoders. (Under Review) [PDF] [CODE]
  5. Zhiding Liu, Jiqian Yang, Mingyue Cheng, Yucong Luo, Zhi Li, Generative Pretrained Hierarchical Transformer for Time Series Forecasting. [PDF]
  6. Jie Wang, Fajie Yuan, Mingyue Cheng, Joemon M. Jose, Chenyun Yu, Beibei Kong, Zhijin Wang, Bo Hu, Zang Li, TransRec: Learning Transferable Recommendation from Mixture-of-Modality Feedback. (Preprint) [PDF]
  7. Hao Zhang, Mingyue Cheng*, Qi Liu, Zhiding Liu, Linbo Zhu, Yu Su, Towards Automatic Sampling of User Behaviors for Sequential Recommender Systems. (Preprint)
  8. Yucong Luo, Mingyue Cheng, Hao Zhang, Junyu Lu, Enhong Chen*, Unlocking the Potential of Large Language Models for Explainable Recommendations. (Accepted, DASFAA2024)
  9. Junzhe Jiang, Shang Qu, Mingyue Cheng*, Qi Liu, Zhiding Liu, Hao Zhang, Rujiao Zhang, Kai Zhang, Rui Li, Jiatong Li, Min Gao, Language Modeling for Content-enriched Recommendation. (Accepted, DASFAA2024)
  10. Mingyue Cheng, Hao Zhang, Qi Liu*, Fajie Yuan, Zhi Li, Zhenya Huang, Enhong Chen, Longfei Li, Jun Zhou, Empowering Sequential Recommender Systems from Mixture of Collaborative Signals and Semantic Relatedness. (Accepted, DASFAA2024)
  11. Hao Zhang, Mingyue Cheng*, Qi Liu, Yucong Luo, Rui Li, Enhong Chen, Learning Recommender Systems with Soft Target: A Decoupled Perspective. (Accepted, DASFAA2024)
  12. Mingyue Cheng, Hao Zhang, Jiqian Yang, Qi Liu*, Li Li, Xin Huang, Liwei Song, Zhi Li, Zhenya Huang, Enhong Chen, Towards Personalized Evaluation of Large Language Models with An Anonymous Crowd-Sourcing Platform. (WWW2024, Accepted)
  13. Junchen Fu, Fajie Yuan, Yu Song, Zheng Yuan, Mingyue Cheng, Shenghui Cheng, Jiaqi Zhang, Jie Wang, Yunzhu Pan, Exploring Adapter-based Transfer Learning for Recommender Systems: Empirical Studies and Practical Insights, (WSDM'2024): 208-217, Mar 4-8, 2024, Mérida, México.
  14. Zhiding Liu, Mingyue Cheng, Zhi Li, Zhenya Huang, Qi Liu, Enhong Chen, Adaptive Normalization for Non-stationary Time Series Forecasting: A Temporal Slice Perspective, The 37th Advances in Neural Information Processing Systems (NeurIPS'2023):36, Dec 9-15, 2023, New Orleans, Louisiana, USA. [PDF] [Code]
  15. 耿杰, 刘春丽*, 魏雪梅, 程明月, 袁昆, 李洋, 刘业政, 基于用户重购行为的产品推荐方法, 计算机研究与发展 2023, 60(8): 1795-1807
  16. Mingyue Cheng, Qi Liu*, Wenyu Zhang, Zhiding Liu, Hongke Zhao, Enhong Chen, A General Tail Item Representation Enhancement Framework for Sequential Recommender Systems, Frontier of Comupter Science (FCS), 2024, 18(6): 1-12. [PDF] [Code]
  17. Mingyue Cheng, Qi Liu*, Zhiding Liu, Zhi Li, Yucong Luo, Enhong Chen, FormerTime: Hierarchical Multi-scale Representation for Multivariate Time Series Classification, The 32nd International World Wide Web Conference (ACM WWW'2023): 1437–1445, Austin, TX, USA. [PDF] [CODE]
  18. Wenqiang He, Mingyue Cheng, Qi Liu*, Zhi Li, ShapeWordNet: An Interpretable Shapelet Neural Network for Physiological Signal Classification, The 28th International Conference on Database Systems for Advanced Applications (DASFAA'2023): 353–369, Tianjin, China.
  19. Mingyue Cheng, Zhiding Liu+, Qi Liu*, Shenyang Ge, Enhong Chen, Towards Automatic Designing of Deep Hybrid Network Architecture for Sequential Recommendation, The 31st International World Wide Web Conference (ACM WWW'2022):1923-1932, Virtual Conference. [CODE]
  20. Zhiding Liu, Mingyue Cheng, Zhi Li, Qi Liu, Enhong Chen*, One Person, One Model—Learning Compound Router for Sequential Recommendation, The 22nd IEEE International Conference on Data Mining (IEEE ICDM'2022).[CODE]
  21. Junzhe Jiang, Mingyue Cheng, Qi Liu*, Zhi Li, Enhong Chen, Nested Named Entity Recognition from Medical Texts: A Multi-task Learning Approach, The Second CAAI International Conference on Artificial Intelligence (CAAI CICAI'2022):248-259, Bejing, China.
  22. Runlong Yu, Qi Liu*, Yuyang Ye, Mingyue Cheng, Enhong Chen, Jianhui Ma, Collaborative List-and-Pairwise Filtering from Implicit Feedback, IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE'2022): 34(6): 2667-2680, June 2022.
  23. Kai Zhang, Qi Liu*, Zhenya Huang, Mingyue Cheng, Kun Zhang, Mengdi Zhang, Wei Wu, Enhong Chen, Graph Adaptive Semantic Transfer for Cross-domain Sentiment Classification, The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (ACM SIGIR'2022): 1566-1576, Virtual Conference.
  24. Mingyue Cheng, Fajie Yuan+, Qi Liu*, Xin Xin, Enhong Chen, Learning Transferrable User Representations with Sequential Behaviors via Contrastive Pre-training, The 21st IEEE International Conference on Data Mining (IEEE ICDM'2021):51-60, Auckland, New Zealand, December 7-10, 2021.
  25. Mingyue Cheng, Fajie Yuan+, Qi Liu*, Shenyang Ge, Zhi Li, Runlong Yu, Defu Lian, Senchao Yuan, Enhong Chen, Learning Recommender Systems with Implicit Feedback via Soft Target Enhancement, The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval ( ACM SIGIR'2021): 575-584, July 11–15, 2021, Virtual Event, Canada.
  26. Linan Yue, Qi Liu*, Han Wu, Kai Zhang, Yanqing An, Mingyue Cheng, Biao Yin, Dayong Wu, NeurJudge: A Circumstance-aware Neural Framework for Legal Judgment Prediction, The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval ( ACM SIGIR'2021):973–982, July 11–15, 2021, Virtual Event, Canada.
  27. Yanqing An, Qi Liu*, Han Wu, Kai Zhang, Linan Yue, Mingyue Cheng, Hongke Zhao, Senchao Yuan, Enhong Chen, LawyerPAN: A Proficiency Assessment Network for Trial Lawyers, The 27th International ACM SIGKDD Conference on Knowledge Discovery and Data Mining (ACM SIGKDD'2021):5-13, August 14–18, 2021, Virtual Event, Singapore.
  28. Mingyue Cheng, Runlong Yu, Qi Liu*, Hongke Zhao, Hefu Zhang, Enhong Chen, Alpha-Beta Sampling for Pairwise Ranking in One-Class Collaborative Filtering, The 19th IEEE International Conference on Data Mining (IEEE ICDM'2019): 1000-1005, Beijing, China.
  29. 程明月, 刘淇*, 李徵, 于润龙, 高维博, 陈恩红, 多重对级贝叶斯个性化排序算法. (南京信息工程大学学报自然科学版: 2019年03期302-308)

Professional Activities

Honors and Awards

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