课程组成员

马千里

博士，教授，博士生导师

- 斯坦福大学与爱思唯尔评选全球前2%顶尖科学家（2023、2024）

- IEEE/ACM TASLP（SCI一区）副主编


电子邮箱：qianlima at scut dot edu dot cn     

主页：http://www2.scut.edu.cn/qianlima

办公电话： (+86)20-39380297转3513        办公室：B7-51

邮寄地址：广州大学城华南理工大学计算机科学与工程学院 510006

 




个人简介

       马千里，博士，教授，博士生导师。2008年6月于华南理工大学获得工学博士学位，同年7月留校任教。2016年3月至2017年3月，为美国加州大学（圣地亚哥分校）访问学者。主要从事人工智能、机器学习和数据挖掘等相关领域的研究工作，已发表文章130余篇，其中多项成果发表在NeurIPS、ICML、ICLR、AAAI、IJCAI、ACL、KDD、ICDE、IEEE TPAMI、IEEE TNNLS等国际顶级会议及期刊上，曾获得CIKM 2022 Best Paper Runner-up。2023、2024连续两年入选美国斯坦福大学与爱思唯尔联合推出的《全球前2%顶尖科学家榜单》。主持国家及省部级项目20余项，参与国家及省部级项目10余项，包括国家重点研发计划项目2项，国家自然科学基金重点项目1项，曾获得广东省科技进步奖二等奖，中国南方电网广东电网公司科技进步二等奖，广东省计算机学会优秀论文一等奖，华南理工大学教学优秀奖一等奖。目前担任国际期刊TASLP的副主编、中国人工智能学会机器学习专委会委员，中国人工智能学会知识工程与分布式智能专委会委员，中国计算机学会人工智能与模式识别专委会委员，以及KDD、IJCAI领域主席（Area Chair）的学术兼职。


研究兴趣

      专注于人工智能、机器学习和数据挖掘领域的研究，特别是在时间序列数据建模、自然语言处理、大模型优化和序列推荐等方面，重点研究鲁棒性高、安全可信的人工智能模型。同时，在产学研合作中，与国家教育部考试院、南方电网、阿里腾讯、机械制造企业等单位开展了“中高考试题查重”、“大模型智能辅助命题”、“电能数据异常诊断与智能修复”、“短视频公众号内容推荐”以及“智能焊机大模型”等众多场景的应用研究工作。


学术/社会兼职：

    IEEE/ACM Transactions on Audio, Speech, and Language Processing (TASLP)副主编

    中国计算机学会（CCF）高级会员，IEEE 会员

    中国人工智能学会机器学习专业委员会委员

    中国人工智能学会知识工程与分布式智能专业委员会委员

    中国计算机学会人工智能与模式识别专业委员会委员


研究成果

Google Scholar

代表论文:

Times Series:

*: 通讯作者

31. Zhen Liu, Peitian Ma, Dongliang Chen, Wenbin Pei, Qianli Ma*. Scale-teaching: Robust Multi-scale Training for Times Series Classification with Noisy Labels[C]//Advances in neural information processing systems (NeurlPS), 2023. [paper][code]

30. Siying Zhu, Jiawei Zheng, Qianli Ma*. MR-Transformer: Multiresolution Transformer for Multivariate Time Series Prediction[J]. IEEE Transactions on Neural Networks and Learning Systems(TNNLS), 2023. [paper]

29. Peitian Ma, Zhen Liu, Junhao Zheng, Linhao Wang, Qianli Ma*. CTW: Confident Time-Warping for Time-Series Label-Noise Learning[C]//IJCAI. 2023: 4046-4054.[paper][code]

28. Zhen Liu, Chuxin Chen, Qianli Ma. Category-aware optimal transport for incomplete data classification[J]. Information Sciences, 2023, 634: 443-476. [paper]

27. Zhen Liu, Qianli Ma*, Peitian Ma, Linghao Wang. Temporal-Frequency Co-training for Time Series Semi-supervised Learning[C]//Proceedings of the AAAI Conference on Artificial Intelligence(AAAI), 2023, 37(7): 8923-8931. [paper][code]

26. Huizi Lyu, Desen Huang, Sen Li, Wing W.Y.Ng, Qianli Ma. Multiscale echo self-attention memory network for multivariate time series classification[J]. Neurocomputing, 2023, 520: 60-72. [paper]

25. Desen Huang, Lifeng Shen, Zhongzhong Yu, Zhenjing Zheng, Min Huang, Qianli Ma*. Efficient time series anomaly detection by multiresolution self-supervised discriminative network[J]. Neurocomputing, 2022, 491: 261-272. [paper]

24. Qianli Ma*, Zipeng Chen, Shuai Tian, Wing W.Y.Ng. Difference-guided representation learning network for multivariate time-series classification[J]. IEEE Transactions on Cybernetics, 2020, 52(6): 4717-4727. [paper]

23. Qianli Ma*, Sen Li, Garrison W.Cottrell. Adversarial joint-learning recurrent neural network for incomplete time series classification[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020, 44(4): 1765-1776. [paper]

22. Zipeng Chen, Qianli Ma*, Zhenxi Lin. Time-Aware Multi-Scale RNNs for Time Series Modeling[C]//IJCAI. 2021: 2285-2291. [paper]

21. Qianli Ma*, Zhenjing Zheng, Jiawei Zheng, Sen Li, Wangqing Zhuang, Garrison W. Cottrell. Joint-Label Learning by Dual Augmentation for Time Series Classification[C]//Proceedings of the AAAI Conference on Artificial Intelligence(AAAI). 2021, 35(10): 8847-8855. [paper]

20. Lifeng Shen, Zhongzhong Yu, Qianli Ma*, James T. Kwok. Time series anomaly detection with multiresolution ensemble decoding[C]//Proceedings of the AAAI Conference on Artificial Intelligence(AAAI). 2021, 35(11): 9567-9575. [paper]

19. Qianli Ma*, Zhenjing Zheng, Wanqing Zhuang, Enhuan Chen, Jia Wei, Jiabing Wang. Echo memory-augmented network for time series classification[J]. Neural Networks, 2021, 133: 177-192. [paper]

18. Qianli Ma*, Sen Li, Garrison W. Cottrell. Adversarial joint-learning recurrent neural network for incomplete time series classification[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence(TPAMI), 2020, 44(4): 1765-1776. [paper]

17. Qianli Ma*, Zipeng Chen, Shuai Tian, Wing W. Y. Ng. Difference-guided representation learning network for multivariate time-series classification[J]. IEEE Transactions on Cybernetics, 2020, 52(6): 4717-4727. [paper]

16. Qianli Ma*, Sen Li, Wanqing Zhuang, Sen Li, Jiabing Wang, Delu Zeng. Self-supervised time series clustering with model-based dynamics[J]. IEEE Transactions on Neural Networks and Learning Systems(TNNLS), 2020, 32(9): 3942-3955. [paper]

15. Qianli Ma*, Zhenxi Lin, Enhuan Chen, Garrison W. Cottrell. Temporal pyramid recurrent neural network[C]//Proceedings of the AAAI Conference on Artificial Intelligence(AAAI). 2020, 34(04): 5061-5068. [paper]

14. Qianli Ma*, Wanqing Zhuang, Sen Li, Desen Huang, Garrison. Adversarial dynamic shapelet networks[C]//Proceedings of the AAAI conference on artificial intelligence(AAAI). 2020, 34(04): 5069-5076. [paper]

13. Qianli Ma*, Jiawei Zheng, Sen Li, Garrison W. Cottrell. Learning representations for time series clustering[J]. Advances in neural information processing systems(NeurlPS), 2019, 32. [paper]

12. Qianli Ma*, Wangqing Zhuang, Garrison W. Cottrell. Triple-shapelet networks for time series classification[C]//2019 IEEE International Conference on Data Mining (ICDM). IEEE, 2019: 1246-1251. [paper]

11. Qianli Ma*, Lifeng Shen, Garrison W. Cottrell. DeePr-ESN: A deep projection-encoding echo-state network[J]. Information Sciences, 2020, 511: 152-171. [paper]

10. Qianli Ma*, Shuai Tian, Jia Wei, Wing W. Y. Ng. Attention-based spatio-temporal dependence learning network[J]. Information Sciences, 2019, 503: 92-108.[paper]

9. Qianli Ma*, Enhuan Chen, Zhenxi Lin, Jiangyue Yan, Zhiwen Yu, Wing W. Y. Ng. Convolutional multitimescale echo state network[J]. IEEE Transactions on Cybernetics, 2019, 51(3): 1613-1625.[paper]

8. Qianli Ma*, Wangqing Zhuang, Lifeng Shen, Garrison W. Cottrell. Time series classification with echo memory networks[J]. Neural networks, 2019, 117: 225-239.[paper]

7. Qianli Ma*, Sen Li, Lifeng Shen, Jiabing Wang, Jia wei, Zhiwen Yu, Garrison W. Cottrell. End-to-end incomplete time-series modeling from linear memory of latent variables[J]. IEEE transactions on cybernetics, 2019, 50(12): 4908-4920.[paper]

6. Kejian Shi, Hongyang Qin, Chijun Sima, Sen Li, Lifeng Shen, Qianli Ma*. Dynamic barycenter averaging kernel in RBF networks for time series classification[J]. IEEE Access, 2019, 7: 47564-47576.[paper]

5. Lifeng Shen, Qianli Ma*, Sen Li. End-to-end time series imputation via residual short paths[C]//Asian conference on machine learning(ACML), 2018: 248-263.[paper]

4. Qianli Ma*, Lifeng Shen, Enhuan Chen, Shuai Tian, Jiabing Wang, Garrison W. Cottrell. WALKING WALKing walking: Action Recognition from Action Echoes[C]//IJCAI. 2017: 2457-2463.[paper]

3. Qianli Ma*, Lifeng Shen, Garrison W. Cottrell. Deep-esn: A multiple projection-encoding hierarchical reservoir computing framework[J]. arXiv preprint arXiv:1711.05255, 2017.[paper]

2. Qianli Ma*, Lifeng Shen, Wanqing Zhuang, Jieyu Chen. Decouple Adversarial Capacities with Dual-Reservoir Network[C]//Neural Information Processing: 24th International Conference, ICONIP 2017, Guangzhou, China, November 14–18, 2017, Proceedings, Part V 24. Springer International Publishing, 2017: 475-483.[paper]

1. Qianli Ma*, Lifeng Shen, Ruishi Su, Jieyu Chen. Two-stage temporal multimodal learning for speaker and speech recognition[C]//Neural Information Processing: 24th International Conference, ICONIP 2017, Guangzhou, China, November 14-18, 2017, Proceedings, Part II 24. Springer International Publishing, 2017: 64-72.[paper]


Natural Language Processing(NLP):

*: 通讯作者

16. Jinsong Yan, Piji Li, Haibin Chen, Junhao Zheng, Qianli Ma*. Does the Order Matter? A Random Generative Way to Learn Label Hierarchy for Hierarchical Text Classification[J]. IEEE/ACM Transactions on Audio, Speech, and Language Processing(TASLP), 2023. [paper]

15. Huawen Feng, Zhenxi Lin, Qianli Ma*. Perturbation-Based Self-Supervised Attention for Attention Bias in Text Classification[J]. IEEE/ACM Transactions on Audio, Speech, and Language Processing(TASLP), 2023, 31: 3139-3151. [paper]

14. Huawen Feng, Junlong Liu, Junhao Zheng, Haibin Chen, Xichen Shang, Qianli Ma*. Joint Constrained Learning with Boundary-adjusting for Emotion-Cause Pair Extraction[C]//Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics(ACL), 2023: 1118-1131. [paper]

13. Junhao Zheng, Qianli Ma*, Shengjie Qiu, Yue Wu, Peitian Ma, Junlong Liu, Huawen Feng, Xichen Shang, Haibin Chen. Preserving Commonsense Knowledge from Pre-trained Language Models via Causal Inference[C]//Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics(ACL), 2023: 9155-9173 [paper]

12. Xichen Shang, Chuxin Chen, Zipeng Chen, Qianli Ma*. Modularized Mutuality Network for Emotion-Cause Pair Extraction[J]. IEEE/ACM Transactions on Audio, Speech, and Language Processing(TASLP), 2022, 31: 539-549. [paper]

11. Junhao Zheng, Haibin Chen, Qianli Ma*. Cross-domain Named Entity Recognition via Graph Matching[C]//Findings of the Association for Computational Linguistics(ACL), 2022. 2022: 2670-2680. [paper]

10. Junlong Liu, Xichen Shang, Qianli Ma*. Pair-Based Joint Encoding with Relational Graph Convolutional Networks for Emotion-Cause Pair Extraction[C]//Conference on Empirical Methods in Natural Language Processing(EMNLP), 2022:5339-5351. [paper]

9. Junhao Zheng, Zhanxian Liang, Haibin Chen, Qianli Ma*. Distilling Causal Effect from Miscellaneous Other-Class for Continual Named Entity Recognition[C]//Conference on Empirical Methods in Natural Language Processing(EMNLP), 2022:3602-3615. [paper][code]

8. Huawen Feng, Qianli Ma*. It’s Better to Teach Fishing than Giving a Fish: An Auto-Augmented Structure-aware Generative Model for Metaphor Detection[C]//Findings of Conference on Empirical Methods in Natural Language Processing(EMNLP), 2022: 656-667. [paper]

7. Haibin Chen, Qianli Ma*, Zhenxi Lin, Jiangyue Yan. Hierarchy-aware label semantics matching network for hierarchical text classification[C]//Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing(ACL) (Volume 1: Long Papers). 2021: 4370-4379. [paper]

6. Xichen Shang, Qianli Ma*, Zhenxi Lin, Jiangyue Yan, Zipeng Chen. A Span-based Dynamic Local Attention Model for Sequential Sentence Classification[C]//Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing(ACL) (Volume 2: Short Papers). 2021: 198-203. [paper]

5. Haibin Chen, Qianli Ma*, Liuhong Yu, Zhenxi Lin, Jiangyue Yan. Corpus-Aware Graph Aggregation Network for Sequence Labeling[J]. IEEE/ACM Transactions on Audio, Speech, and Language Processing(TASLP), 2021, 29: 2048-2057. [paper]

4. Qianli Ma*, Jiangyue Yan, Zhenxi Lin, Liuhong Yu, Zipeng Chen. Deformable Self-Attention for Text Classification[J]. IEEE/ACM Transactions on Audio, Speech, and Language Processing(TASLP), 2021, 29: 1570-1581. [paper]

3. Qianli Ma*, Zhenxi Lin, Jiangyue Yan, Zipeng Chen, Liuhong Yu. Mode-LSTM: a parameter-efficient recurrent network with multi-scale for sentence classification[C]//Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP). 2020: 6705-6715. [paper]

2. Qianli Ma*, Liuhong Yu, Shuai Tian, Enhuan Chen, Wing W. Y. Ng. Global-local mutual attention model for text classification[J]. IEEE/ACM Transactions on Audio, Speech, and Language Processing(TASLP), 2019, 27(12): 2127-2139. [paper]

1. Luoqin Li, Jiabing Wang, Jichang Li, Qianli Ma*, Jia Wei. Relation classification via keyword-attentive sentence mechanism and synthetic stimulation loss[J]. IEEE/ACM Transactions on Audio, Speech, and Language Processing(TASLP), 2019, 27(9): 1392-1404. [paper]


Others:

4. Sen Li, Fuyu Lv, Taiwei Jin, Yukun Zheng, Tao Zhuang, Qingwen Liu, Xiaoyi Zeng, James T.Kwok, Qianli Ma*. Query Rewriting in TaoBao Search[C]//Proceedings of the 31st ACM International Conference on Information & Knowledge Management(CIKM). 2022: 3262-3271. [paper]

3. Jiawei Zheng, Qianli Ma*, Hao Gu, Zhenjing Zheng. Multi-view denoising graph auto-encoders on heterogeneous information networks for cold-start recommendation[C]//Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining(KDD). 2021: 2338-2348. [paper]

2. Sen Li, Fuyu Lv, Taiwei Jin, Guli Lin, Keping Yang, Xiaoyi Zeng, Xiaoming Wu, Qianli Ma*. Embedding-based product retrieval in taobao search[C]//Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining(KDD). 2021: 3181-3189. [paper]

1. Wenguang Yuan, Jia Wei, Jiabing Wang, Qianli Ma, Tolga Tasdizen. Unified attentional generative adversarial network for brain tumor segmentation from multimodal unpaired images[C]//Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd International Conference, Shenzhen, China, October 13–17, 2019, Proceedings, Part III 22. Springer International Publishing, 2019: 229-237. [paper]


部分项目：

1. 广东省科技计划项目(国际科技合作领域). “面向大规模时间序列数据表示学习的研究”，编号：2023A0505050106，项目起止时间：2023年9月-2025年9月.

2. 南方电网科研院项目，“配电网智能交互框架及边缘计算资源分配关键技术研究”，编号：2023440002001056，项目起止时间：2023年4月-2024年9月.

3. 国家自然科学基金面上项目,“面向低质量时间序列的鲁棒性表示学习”, 编号：62272173，项目起止时间：2023

年1月-2026年12月.

4. 广东省自然科学基金面上项目，“面向现实复杂场景中的时间序列数据建模”，编号：2022A1515010179，项

目起止时间：2022年1月-2024年12月.

5. 国家自然科学基金项目，“基于高维随机投影的深度储备池计算模型研究”，编号：61872148，项目起止时间：2019年1月-2022年12月。

6. 国家自然科学基金项目，“多尺度模块网络下的储备池神经计算模型及算法研究”，编号：61502174，项目起止时间：2016年1月-2018年12月。

7. 广州市科技计划项目-产学研协同创新重大专项，“基于深度学习的商业智能分析平台关键技术研发”，编号：201704030051，项目起止时间：2017年5月-2019年12月。


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实验室成员


在读学生

博士生

  • 2025 蔡希迪

  • 2024 黎泊远

  • 2023 吴斌权

  • 2022 郑俊豪 邝涛杰 冯华文

  • 2021 柳真 


硕士生

  • 2025 李秋科 苏琪 张少为 柯宇浩

  • 2024 侯晓文 曾坤 姚泽坤 施成明

  • 2023 邱圣洁 吴钺 罗奕城 陈家豪

  • 2022 刘俊龙 张崇志 严景松 汪灵浩

  • 2021 袁海桃 刘嘉麒 程雨



已毕业学生

  • 2020 陈海斌（@阿里） 陈楚鑫（@阿里） 朱思颖（@腾讯） 尚曦辰（@字节） 


  • 2019 郑佳炜（@腾讯） 郑镇境（@腾讯） 陈子鹏（@蚂蚁） 余忠忠（@字节）


  • 2018 黄德森（@百度） 李森（@字节） 林镇溪（@腾讯） 闫江月（@京东）


  • 2017 余柳红（@华为） 庄万青（@腾讯） 李森（@阿里）


  • 2016 陈恩欢（@字节） 田帅（@微信）


  • 2015 沈礼锋（@重庆邮电大学教师）


  • 2012 蒋佳军（@百度)


  • 2010 陈威彪（@民航局）


  • 2009 林泽鑫（联合指导，@易方达基金)   周卫敏（联合指导，@中兴）


  • 2008 吴广财（联合指导，@广东电网） 郑杰生（联合指导，@广东电网）


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教授课程：离散数学、深度学习


招生要求(本科生SRP、实习、研究生等）:

    1.对人工智能领域感兴趣；成绩好；逻辑思维清晰；算法编程能力强；能不太困难的阅读英文文献；能吃苦

    2.修读或自学过以下课程：

       线性代数   概率统计   算法分析与设计   机器学习

    3.掌握至少一门工具：C++、JAVA、Python、Matlab

    4.参加过ACM竞赛、数模竞赛等（此项非必备条件）

     5.需要本人写推荐信的同学请注意，为了使推荐信评价更客观公正，本人只给在我们组至少工作过6个月（含）以上的同学写推荐信，请谅解。