Xingyu Wu 吴兴宇

Xingyu Wu 吴兴宇

Postdoctoral Fellow, PolyU

Dr. Xingyu Wu is a postdoctoral fellow in the Department of Data Science and Artificial Intelligence, The Hong Kong Polytechnic University (PolyU), Hong Kong SAR, China. Before joining PolyU, he received the Bachelor degree from the School of Computer Science and Engineering, University of Electronic Science and Technology of China (UESTC), Chengdu, China, in 2018, and PhD degree from School of Computer Science and Technology, University of Science and Technology of China (USTC), Hefei, China, in 2023. Dr. Wu is currently affiliated with the MIND Lab@PolyU, which is dedicated to advancing the frontiers of nature-inspired artificial intelligence research. He is fortunate to be advised by Prof. Kay Chen Tan and Prof. Jibin Wu in MIND Lab. His research interests encompass a wide range of areas, focusing on causality-based machine learning, automatic machine learning, and large foundation model.

Dr. Wu has actively published in prestigious conferences and journals in machine learning and data mining, including AAAI, IJCAI, ICML, NeurIPS, CIKM, MM, TPAMI, TNNLS, TEVC, TCYB, TETCI, TKDD, Information Sciences, and Information Fusion. He is currently serving as the reviewer for 20+ prestigious journals, and program committee member for 10+ top conferences. For anything about the research, resources, and other related matters, please feel free to contact him via Wechat (wuxingyu-uestc) or Email (xingy.wu@polyu.edu.hk).

📝 Publications

  1. Xingyu Wu, Sheng-hao Wu, Jibin Wu, Liang Feng, Kay Chen Tan. Evolutionary Computation in the Era of Large Language Model: Survey and Roadmap. IEEE Transactions on Evolutionary Computation, vol X (x), pp. xxxx-xxxx, 2024. (Repository)
  2. Zhaolong Ling, Bo Li, Yiwen Zhang, Peng Zhou, Xingyu Wu, Kui Yu, Xindong Wu. Causal Discovery Using Weight-Based Conditional Independence Test. ACM Transactions on Knowledge Discovery from Data, vol X (x), pp. xxxx-xxxx, 2024.
  3. Chenglong Zhang, Xinyan Liang, Peng Zhou, Zhaolong Ling, Yingwei Zhang, Xingyu Wu, Weiguo Sheng, Bingbing Jiang. Scalable Multi-view Unsupervised Feature Selection with Structure Learning and Fusion. The 32nd ACM International Conference on Multimedia (MM’24), 28 October - 1 November, 2024, Melbourne, Australia.
  4. Li Zhang, Zean Han, Yan Zhong, Qiaojun Yu, Xingyu Wu, Xue Wang, RujingWang. VoCAPTER: Voting-based Pose Tracking for Category-level Articulated Object via Inter-frame Priors. The 32nd ACM International Conference on Multimedia (MM’24), 28 October - 1 November, 2024, Melbourne, Australia.
  5. Yan Zhong, Xingyu Wu, Li Zhang, Chenxi Yang, Tingting Jiang. Causal-IQA: Towards the Generalization of Image Quality Assessment Based on Causal Inference. The 41st International Conference on Machine Learning (ICML’24), July 21-27, 2024, Vienna, Austria.
  6. Xingyu Wu, Yan Zhong, Jibin Wu, Bingbing Jiang, Kay Chen Tan. Large Language Model-Enhanced Algorithm Selection: Towards Comprehensive Algorithm Representation. The 33rd International Joint Conference on Artificial Intelligence (IJCAI’24), August 3-9, 2024, Jeju, South Korea.
  7. Chenglong Zhang, Yang Fang, Xinyan Liang, Han Zhang, Peng Zhou, Xingyu Wu, Jie Yang, Bingbing Jiang, Weiguo Sheng. Efficient Multi-view Unsupervised Feature Selection with Adaptive Structure Learning and Inference. The 33rd International Joint Conference on Artificial Intelligence (IJCAI’24), August 3-9, 2024, Jeju, South Korea.
  8. Xingyu Wu, Yan Zhong, Zhaolong Ling, Jie Yang, Li Li, Weiguo Sheng, Bingbing Jiang. Nonlinear Learning Methods for Local Causal Structures. Information Sciences, vol. 654 (1), pp. 119789, 2024.
  9. Chenglong Zhang, Bingbing Jiang, Zidong Wang, Jie Yang, Yangfeng Lu, Xingyu Wu, Weiguo Sheng. Efficient multi-view semi-supervised feature selection. Information Sciences, vol 649 (11), pp. 119675, 2023.
  10. Bingbing Jiang, Chenglong Zhang, Yan Zhong, Yi Liu, Yingwei Zhang, Xingyu Wu *, Weiguo Sheng *. Adaptive Collaborative Fusion for Multi-view Semi-supervised Classification. Information Fusion, vol 96 (8), pp. 37 - 50, 2023.
  11. Shengfei Lyu, Xiren Zhou, Xingyu Wu, Qiuju Chen, Huanhuan Chen. Self-Attention Over Tree for Relation Extraction With Data-Efficiency and Computational Efficiency. IEEE Transactions on Emerging Topics in Computational Intelligence, vol. 8 (2), pp. 1253 - 1263, 2024.
  12. Xingyu Wu, Bingbing Jiang, Xiangyu Wang, Taiyu Ban, Huanhuan Chen. Feature Selection in the Data Stream Based on Incremental Markov Boundary Learning. IEEE Transactions on Neural Networks and Learning Systems, vol. 34 (10), pp. 6740 - 6754, 2023.
  13. Xiangyu Wang, Lyuzhou Chen, Taiyu Ban, Derui Lyu, Yifeng Guan, Xingyu Wu, Xiren Zhou, Huanhuan Chen. Accurate Label Refinement from Multi-Annotator of Remote Sensing Data. IEEE Transactions on Geoscience and Remote Sensing, vol. 61, pp. 4700413, 2023.
  14. Xingyu Wu, Bingbing Jiang, Tianhao Wu, Huanhuan Chen. Practical Markov Boundary Learning without Strong Assumptions. The 37th AAAI Conference on Artificial Intelligence (AAAI’23), February 7-14, 2023, Washington, DC, USA.
  15. Xin Wang, Shengfei Lyu, Xiangyu Wang, Xingyu Wu, Huanhuan Chen. Temporal Knowledge Graph Embedding via Sparse Transfer Matrix. Information Sciences, vol. 623, no. 4, pp. 56–69, 2023.
  16. Xin Wang, Shengfei Lyu, Xingyu Wu, Tianhao Wu, Huanhuan Chen. Generalization Bounds for Estimating Causal Effects of Continuous Treatments. The 36th Conference on Neural Information Processing Systems (NeurIPS’22), November 29 - December 1, 2022, New Orleans, Louisiana, USA.
  17. Xiangyu Wang, Taiyu Ban, Lyuzhou Chen, Xingyu Wu, Derui Lyu, Huanhuan Chen. Knowledge Verification from Data. IEEE Transactions on Neural Networks and Learning Systems, vol. 35, no. 3, pp. 4324 - 4338, 2024.
  18. Xingyu Wu, Bingbing Jiang, Yan Zhong, Huanhuan Chen. Multi-target Markov Boundary Discovery: Theory, Algorithm, and Application. IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 45, no. 4, pp. 4964 - 4980, 2023.
  19. Bingbing Jiang, Junhao Xiang, Xingyu Wu, Yadi Wang, Huanhuan Chen, Yi Liu, Weiwei Cao, Weiguo Sheng. Robust Multi-view Learning via Adaptive Regression. Information Sciences, vol. 610, no. 9, pp. 916–937, 2022.
  20. Tianhao Wu, Xingyu Wu, Xin Wang, Shikang Liu, Huanhuan Chen. Nonlinear Causal Discovery in Time Series. The 31st ACM International Conference on Information and Knowledge Management (CIKM’22), October 17–21, 2022, Atlanta, Georgia, USA.
  21. Bingbing Jiang, Xingyu Wu, Xiren Zhou, Anthony Cohn, Yi Liu, Weiguo Sheng, Huanhuan Chen. Semi-Supervised Multi-View Feature Selection with Adaptive Graph Learning. IEEE Transactions on Neural Networks and Learning Systems, vol. 35, no. 3, pp. 3615 - 3629, 2024.
  22. Taiyu Ban, Xiangyu Wang, Lyuzhou Chen, Xingyu Wu, Qiuju Chen, Huanhuan Chen. Quality Evaluation of Triples in Knowledge Graph by Incorporating Internal with External Consistency. IEEE Transactions on Neural Networks and Learning Systems, vol. 35, no. 2, pp. 1980 - 1992, 2024.
  23. Xingyu Wu, Zhenchao Tao, Bingbing Jiang, Tianhao Wu, Xin Wang, Huanhuan Chen. Domain Knowledge-enhanced Variable Selection for Biomedical Data Analysis. Information Sciences, vol. 606 (8), pp. 469 - 488, 2022.
  24. Jiarun Zhu, Xingyu Wu, Muhammad Usman, Xiangyu Wang, Huanhuan Chen. Link Prediction in Continuous-Time Dynamic Heterogeneous Graphs with Causality of Event Types. International Journal of Crowd Science, vol. 6, no. 2, pp. 80–91, 2022.
  25. Xingyu Wu, Bingbing Jiang, Shengfei Lyu, Xiangyu Wang, Qiuju Chen, Huanhuan Chen. A Survey on Causal Feature Selection Based on Markov Boundary Discovery. Pattern Recognition and Artificial Intelligence, vol. 35 (5), pp. 422 - 438, 2022.
  26. Gangqiang Hu, Shengfei Lyu, Xingyu Wu, Jinlong Li, Huanhuan Chen. Contextual-Aware Information Extractor with Adaptive Objective for Chinese Medical Dialogues. ACM Transactions on Asian and Low-Resource Language Information Processing, vol. 21 (5), pp. 1 - 21, 2022.
  27. Bingbing Jiang, Wenda He, Xingyu Wu, Junhao Xiang, Libin Hong, Weiguo Sheng. Semi-Supervised Feature Selection with Adaptive Graph Learning. ACTA Electronica Sinica, vol. 50, no. 7, pp. 1643–1652, 2022.
  28. Shengfei Lyu, Xingyu Wu, Jinlong Li, Qiuju Chen, Huanhuan Chen. Do Models Learn the Directionality of Relations? A New Evaluation: Relation Direction Recognition. IEEE Transactions on Emerging Topics in Computational Intelligence, vol. 6 (4), pp. 883 - 892, 2022.
  29. Kui Yu, Mingzhu Cai, Xingyu Wu, Lin Liu, Jiuyong Li. Multi-Label Feature Selection: a Local Causal Structure Learning Approach. IEEE Transactions on Neural Networks and Learning Systems, vol. 34 (6), pp. 3044 - 3057, 2023.
  30. Bingbing Jiang, Junhao Xiang, Xingyu Wu *, Wenda He, Libin Hong, Weiguo Sheng *. Robust Adaptive-weighting Multi-view Classification. The 30th ACM International Conference on Information and Knowledge Management (CIKM’21), November 1–5, 2021, Gold Coast, Australia.
  31. Yan Zhong, Xingyu Wu, Bingbing Jiang, Huanhuan Chen. Multi-label Local-to-Global Feature Selection. International Joint Conference on Neural Networks (IJCNN’21), July 18–22, 2021, Virtual Event, Shenzhen, China.
  32. Xingyu Wu, Bingbing Jiang, Kui Yu, Huanhuan Chen. Separation and Recovery Markov Boundary Discovery and Its Application in EEG-based Emotion Recognition. Information Sciences, vol. 571 (9), pp. 262 - 278, 2021.
  33. Shengfei Lyu, Jin Cheng, Xingyu Wu, Lizhen Cui, Huanhuan Chen, Chunyan Miao. Auxiliary Learning for Relation Extraction. IEEE Transactions on Emerging Topics in Computational Intelligence, vol. 6 (1), pp. 182 - 191, 2022.
  34. Xingyu Wu, Bingbing Jiang, Yan Zhong, Huanhuan Chen. Tolerant Markov Boundary Discovery for Feature Selection. The 29th ACM International Conference on Information and Knowledge Management (CIKM’20), October 19–23, 2020, Virtual Event, Ireland.
  35. Xingyu Wu, Bingbing Jiang, Kui Yu, Huanhuan Chen, Chunyan Miao. Multi-label Causal Feature Selection. The 34th AAAI Conference on Artificial Intelligence (AAAI’20), February 7-12, 2020, New York, USA.
  36. Xingyu Wu, Bingbing Jiang, Kui Yu, Chunyan Miao, Huanhuan Chen. Accurate Markov Boundary Discovery for Causal Feature Selection. IEEE Transactions on Cybernetics, vol. 50 (12), pp. 4983 - 4996, 2020.
  37. Bingbing Jiang, Xingyu Wu, Kui Yu, Huanhuan Chen. Joint Semi-supervised Feature Selection and Classification through Bayesian Approach. The 33th AAAI Conference on Artificial Intelligence (AAAI’19), January 27- February 1, 2019, Honolulu, Hawaii, USA.

    Note: * indicates the corresponding author. Some papers are Under Review.

📖 Educations

  • 2014.09 - 2018.06, University of Electronic Science and Technology of China, Bachelor
    • Computer Science and Technology, School of Computer Science and Engineering
  • 2018.09 - 2023.06, University of Science and Technology of China, Ph.D.
    • Computer Science and Technology, School of Computer Science and Technology

💻 Research

  • Causality-based Machine Learning
  • Automatic Machine Learning
  • Large Foundation Model

🎖 Honors and Awards

  • National Scholarship, Ministry of Education of the People’s Republic of China, Dec 2016, Dec 2019
  • Outstanding Graduate Award of Sichuan Province, Education Department of Sichuan Province, Jan 2018
  • Outstanding Graduate Award of UESTC, UESTC, Jun 2018
  • AAAI 2020 Travel Award, AAAI, Jan 2020
  • Huawei Scholarship, Huawei, Dec 2020, Dec 2022
  • Intel Scholarship, Intel, Dec 2022
  • Top Performance Award, ACM Multimedia 2022 Social Media Prediction (SMP) Challenge, Dec 2022
  • CAST 2022 Annual Science and Technology Journal Bilingual Dissemination Project, China Association for Science and Technology, Dec, 2022
  • Outstanding Graduate Award of USTC, USTC, Jun 2023

⏳ Professional Services

Program Committee Members

  • The 35th AAAI Conference on Artificial Intelligence (AAAI’21)
  • The 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP’21)
  • The 36th AAAI Conference on Artificial Intelligence (AAAI’22)
  • The 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP’22)
  • The 2023 Future of Information and Communication Conference (FICC’23)
  • The 37th AAAI Conference on Artificial Intelligence (AAAI’23)
  • The 2023 International Joint Conference on Neural Networks (IJCNN’23)
  • The 38th AAAI Conference on Artificial Intelligence (AAAI’24)
  • The 2024 International Joint Conference on Neural Networks (IJCNN’24)
  • The 33rd International Joint Conference on Artificial Intelligence (IJCAI’24)
  • The 33rd ACM International Conference on Multimedia (ACM MM’24)
  • The 11th IEEE International Conference on Cybernetics and Intelligent Systems Robotics, Automation and Mechatronics (CIS-RAM’24), Associate Editor
  • The 38th Annual Conference on Neural Information Processing Systems (NeurIPS’24)
  • The 13th International Conference on Learning Representations (ICLR’25)
  • The 28th International Conference on Artificial Intelligence and Statistics (AISTATS’25)

Journal Invited Reviewer

  • IEEE Transactions on Knowledge and Data Engineering (TKDE, IEEE)
  • IEEE Transactions on Neural Networks and Learning Systems (TNNLS, IEEE)
  • IEEE Transactions on Evolutionary Computation (TEVC, IEEE)
  • IEEE Transactions on Cybernetics (TCYB, IEEE)
  • IEEE Transactions on Cognitive and Developmental Systems (TCDS, IEEE)
  • IEEE/CAA Journal of Automatica Sinica (JAS, IEEE)
  • INFORMS Journal on Computing (JOC, INFORMS, UTD-24 Journal)
  • Information Fusion (INFFUS, Elsevier)
  • Pattern Recognition (PR, Elsevier)
  • Neurocomputing (NEUCOM, Elsevier)
  • Electronic Commerce Research and Applications (ECRA, Elsevier)
  • ARRAY (ARRAY, Elsevier)
  • World Wide Web (WWW, Springer)
  • Soft Computing (SOCO, Springer)
  • International Journal of Fuzzy Systems (IJFS, Springer)
  • Journal of Ambient Intelligence and Humanized Computing (AIHC, Springer)
  • International Journal of Intelligent Systems (IJIS, Wiley)
  • Intelligent Automation and Soft Computing (IASC, TSI Press)
  • CMC-Computers, Materials & Continua (CMC, Tech Science Press)
  • JMIR Medical Informatics (JMI, JMIR)