我目前在合肥工业大学计算机与信息学院攻读博士学位👨‍🎓。 我的研究兴趣主要包括😎😎😎: ✔️ 因果发现 (Causal Discovery) 因果特征选择 (Causal Feature Selection) 因果结构学习 (Causal Structure Learning) ✔️ 联邦学习 (Federated Learning) 联邦因果发现 (Federated Causal Discovery) 🔜 可信人工智能 (Trustworthy Artificail Intelligence)

📧 [E-mail] 🎓 [Google Scholar] 📥 [GitHub] 🆔 [ORCID] 📑 [English Page]

教育经历

• 2021.09 ~ 现在: 合肥工业大学, 计算机与信息学院, 在读博士 [导师: 💁‍♂️俞奎教授👍]

• 2023.10 ~ 2024.10: 新加坡南洋理工大学, 计算与数据科学学院, 访问博士 (CSC) [导师: 💁‍♂️Han Yu教授👍]

• 2018.09 ~ 2021.07: 合肥工业大学, 计算机与信息学院, 硕士

• 2014.09 ~ 2018.07: 安徽师范大学, 计算机与信息学院, 学士

学术论文

2025

• Federated Causally Invariant Feature Learning
  Xianjie Guo, Kui Yu, Lizhen Cui, Han Yu, and Xiaoxiao Li
  Proceedings of the 39th AAAI Conference on Artificial Intelligence (AAAI'25), 2025.
  [CCF A类会议, 录用率约23.40%] 相关下载链接: [PDF][Code][Appendix]

2024

• Enhancing Causal Discovery in Federated Settings with Limited Local Samples
  Xianjie Guo, Liping Yi, Xiaohu Wu, Kui Yu, and Gang Wang
  International Workshop on Federated Foundation Models in Conjunction with NeurIPS 2024 (FL@FM-NeurIPS), 2024.
  [顶会Workshop, 优秀学生论文奖, 口头汇报] 相关下载链接: [PDF][Code]

• Progressive Skeleton Learning for Effective Local-to-Global Causal Structure Learning
  Xianjie Guo, Kui Yu, Lin Liu, Jiuyong Li, Jiye Liang, Fuyuan Cao, and Xindong Wu
  IEEE Transactions on Knowledge and Data Engineering (TKDE), 2024.
  [CCF A类期刊] 相关下载链接: [PDF][Code][Supplementary Material]

• Sample Quality Heterogeneity-aware Federated Causal Discovery through Adaptive Variable Space Selection
  Xianjie Guo, Kui Yu, Hao Wang, Lizhen Cui, Han Yu, and Xiaoxiao Li
  Proceedings of the 33rd International Joint Conference on Artificial Intelligence (IJCAI'24), 2024.
  [CCF A类会议, 录用率约14.00%, (长) 口头汇报] 相关下载链接: [PDF][Code][Appendix]

• FedCSL: A Scalable and Accurate Approach to Federated Causal Structure Learning
  Xianjie Guo, Kui Yu, Lin Liu, and Jiuyong Li
  Proceedings of the 38th AAAI Conference on Artificial Intelligence (AAAI'24), 2024.
  [CCF A类会议, 录用率约23.75%] 相关下载链接: [PDF][Code][Appendix]

• Local Causal Structure Learning with Missing Data
  Shaojing Sheng, Xianjie Guo, Kui Yu, and Xindong Wu
  Expert Systems With Applications (ESWA), 2024.
  [SCI一区, 影响因子: 7.5, CCF C类期刊] 相关下载链接: [PDF]

2023

• Adaptive Skeleton Construction for Accurate DAG Learning
  Xianjie Guo, Kui Yu, Lin Liu, Peipei Li, and Jiuyong Li
  IEEE Transactions on Knowledge and Data Engineering (TKDE), 2023.
  [CCF A类期刊] 相关下载链接: [PDF][Code][Supplementary Material]

• Towards Privacy-Aware Causal Structure Learning in Federated Setting
  Jianli Huang, Xianjie Guo (co-first author), Kui Yu, Fuyuan Cao, and Jiye Liang
  IEEE Transactions on Big Data (TBD), 2023.
  [SCI二区, 影响因子: 7.5, CCF C类期刊] 相关下载链接: [PDF][Code][Supplementary Material]

• Causal Feature Selection in the Presence of Sample Selection Bias
  Shuai Yang, Xianjie Guo, Kui Yu, Xiaoling Huang, Tingting Jiang, Jin He, and Lichuan Gu
  ACM Transactions on Intelligent Systems and Technology (TIST), 2023.
  [SCI四区, 影响因子: 7.2] 相关下载链接: [PDF]

• A novel data enhancement approach to DAG learning with small data samples
  Xiaoling Huang, Xianjie Guo, Yuling Li, and Kui Yu
  Applied Intelligence (APIN), 2023.
  [SCI二区, 影响因子: 3.4, CCF C类期刊] 相关下载链接: [PDF]

• Bootstrap-based Layer-wise Refining for Causal Structure Learning
  Guodu Xiang, Hao Wang, Kui Yu, Xianjie Guo, Fuyuan Cao, and Yukun Song
  IEEE Transactions on Artificial Intelligence (TAI), 2023.
  [EI期刊] 相关下载链接: [PDF][Code]

2022

• Bootstrap-based Causal Structure Learning
  Xianjie Guo, Yujie Wang, Xiaoling Huang, Shuai Yang, and Kui Yu
  Proceedings of the 31st ACM International Conference on Information & Knowledge Management (CIKM'22), 2022.
  [CCF B类会议, 长文, 录用率约21.6%] 相关下载链接: [PDF][Code]

• Causal Feature Selection With Dual Correction
  Xianjie Guo, Kui Yu, Lin Liu, Fuyuan Cao, and Jiuyong Li
  IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022.
  [SCI一区, 影响因子: 10.2, CCF B类期刊] 相关下载链接: [PDF][Code][Supplementary Material]

• Error-aware Markov blanket learning for causal feature selection
  Xianjie Guo, Kui Yu, Fuyuan Cao, Peipei Li, and Hao Wang
  Information Sciences (INS), 2022.
  [SCI一区, 影响因子: 8.1, CCF B类期刊] 相关下载链接: [PDF][Code]

2021

• Accelerating Learning Bayesian Network Structures by Reducing Redundant CI Tests
  Wentao Hu, Shuai Yang, Xianjie Guo, and Kui Yu
  2021 IEEE International Conference on Big Knowledge (ICBK), 2021.
  [EI会议] 相关下载链接: [PDF]

• Improving Gradient-based DAG Learning by Structural Asymmetry
  Yujie Wang, Shuai Yang, Xianjie Guo, and Kui Yu
  2021 IEEE International Conference on Big Knowledge (ICBK), 2021.
  [EI会议] 相关下载链接: [PDF]

2020

• Causality-based Feature Selection: Methods and Evaluations
  Kui Yu, Xianjie Guo, Lin Liu, Jiuyong Li, Hao Wang, Zhaolong Ling, and Xindong Wu
  ACM Computing Surveys (CSUR), 2020.
  [SCI一区, 影响因子: 23.8] 相关下载链接: [PDF][Code][Supplementary Material]

荣誉奖励

• 硕士研究生国家奖学金 [排名: 3rd / 15] (2020.11)

• 博士研究生国家奖学金 [排名: 1st / 6] (2024.09)

• 安徽省优秀毕业生称号 (2021.05)

• 合肥工业大学优秀毕业生称号 (2021.05)

• 2021年度安徽省计算机学会优秀硕士论文奖 (2021.12)

• 2022年度安徽省优秀硕士学位论文奖 (2022.12)

• 2023年度国家留学基金委公派留学奖学金 (2023.08)

• 2023年度安徽省新时代育人质量工程项目-研究生学术创新: 面向医疗数据的联邦因果发现 (No. 2023xscx012), 申报负责人

• 2024年度安徽省新时代育人质量工程项目-研究生“创新创业之星”

• FL@FM-NeurIPS'24 优秀学生论文奖 (2024.10)

课题项目

• 面向隐私保护数据的联邦因果关系推断算法研究 (No. 62376087), 2024.01-2027.12
  项目骨干; 经费:51万元
  国家自然科学基金面上项目
  

• 跨媒体因果推断与可信机器学习 (No. 2021ZD0111801), 2021.12-2025.11
  子课题骨干; 经费:180万元
  科技部科技创新2030-“新一代人工智能”重大项目
  

• 常识知识学习与因果分析 (No. 2020AAA0106100), 2020.11-2024.10
  课题骨干; 经费:180万元
  科技部科技创新2030-“新一代人工智能”重大项目
  

学术服务

期刊审稿

• IEEE Transactions on Knowledge and Data Engineering

• IEEE Transactions on Neural Networks and Learning Systems

• ACM Transactions on Knowledge Discovery from Data

• IEEE Transactions on Signal and Information Processing over Networks

• IEEE Transactions on Emerging Topics in Computational Intelligence

• Machine Learning

• Neurocomputing

• Applied Intelligence

• International Journal of Machine Learning and Cybernetics

• The Journal of Supercomputing

• Intelligent Automation and Soft Computing

• CMC-Computers Materials & Continua

• Neural Processing Letters

会议审稿

• International Conference on Machine Learning (ICML'25), PC Member

• International Conference on Learning Representations (ICLR'25), PC Member

• Association for the Advancement of Artificial Intelligence (AAAI'24-25), PC Member

• International Joint Conference on Artificial Intelligence (IJCAI'24), PC Member

• The International Workshop on Federated Learning in the Age of Foundation Models (FL@FM-NeurIPS'23), PC Member

• The International Workshop on Federated Foundation Models for the Web 2024 (FL@FM-TheWebConf'24), PC Member

• The International Workshop on Trustworthy Federated Learning in Conjunction with IJCAI 2023 (FL-IJCAI'23), PC Member

• The International Workshop on Federated Learning and Foundation Models (FL@FM-ICME'24), PC Member

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