因果学习

统计独立性分析

人工智能可解释性

多模态医学数据分析

2015 ~ 2020   复旦大学 & Carnegie Mellon University   联合培养博士

2012 ~ 2015   广东工业大学   硕士

2007 ~ 2011   广东工业大学   本科

   

• Yixin Ren, Haocheng Zhang, Yewei Xia, Hao Zhang*, Jihong Guan, Shuigeng Zhou. Fast Causal Discovery by Approximate Kernel-based Generalized Score Functions with Linear Computational Complexity. In: Proceedings of 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2025, Accepted.

• Yixin Ren, Yewei Xia, Hao Zhang*, Jihong Guan, Shuigeng Zhou. Efficiently Learning Significant Fourier Feature Pairs for Statistical Independence Testing. In: Proceedings of the Thirty-Eighth Annual Conference on Neural Information Processing Systems (NeurIPS), 2024, Accepted.

• Hao Zhang, Yixin Ren, Yewei Xia, Shuigeng Zhou, Jihong Guan. Towards Effective Causal Partitioning by Edge Cutting of Adjoint Graph. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024, doi: 10.1109/TPAMI.2024.3435503.

• Mingjie Chen, Hongcheng Wang, Ruxin Wang, Yuzhong Peng, Hao Zhang*. CDRM: Causal Disentangled Representation Learning for Missing Data. Knowledge-Based Systems (KBS), 2024, Volume 299, 5, 112079.

• Ru Zhang, Yanmei Lin, Yijia Wu, Lei Deng, Hao Zhang*, Mingzhi Liao, Yuzhong Peng, MvMRL: A Multi-view Molecular Representation Learning Method for Molecular Property Prediction. Briefings in Bioinformatics (BIB), 2024, Volume 25, Issue 4, July, bbae298, doi.org/10.1093/bib/bbae298.

• Yuanpeng Zeng, Yuzhong Peng, Ru Zhang, Hao Zhang*, Shaojie Qiao, Faliang Huang, Qing Tian. GCCNet: A Novel Network Leveraging Gated Cross-Correlation for Multi-View Classification. IEEE Transactions on Multimedia (TMM), Accepted on 17-Aug-2024.

• Wenwei Xu, Hao Zhang*, Yewei Xia, Yixin Ren, Shiugeng Zhou, Jihong Guan. Hybrid Causal Feature Selection for Cancer Biomarker Identification from RNA-seq Data. IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB). 2024, May, doi: 10.1109/TCBB.2024.3406922.

• Yixin Ren, Yewei Xia, Hao Zhang*, Jihong Guan, Shuigeng Zhou. Learning Adaptive Kernels for Statistical Independence Test. In: Proceedings of  the International Conference on Artificial Intelligence and Statistics (AISTATS). PMLR, 2024: 2494-2502.

• Shaofan Chen, Yuzhong Peng, Guoyuan He, Hao Zhang*, Li Cai, Chengdong Wei. CDSC: Causal Decomposition Based on Spectral Clustering. Information Sciences (INS), 2024, 657: 119985.

• Wen Zheng, Zhongji Li, Yuanyuan Chen, Lei Deng, Hao Zhang, Yuzhong Peng. CDRM: GEP-DNN4Mol: Automatic Chemical Molecular Design Based on Deep Neural Networks and Gene Expression Programming. International Symposium on Bioinformatics Research and Application (ISBRA), 2024, Accepted.

• Hao Zhang, Chuanxu Yan, Yewei Xia, Shuigeng Zhou, Jihong Guan. Causal Gene Identification Using Non-linear Regression-based Independence Tests. IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), 2023, 10(1), 185-195.

• Yuzhong Peng, Hao Zhang*, Ziqiao Zhang, Yanmei Lin, Shuigeng Zhou, Shaojie Qiao. GEP-DL4Mol: A Novel Molecular Deep-learning Model Optimization Framework for Boosting Molecular Properties Prediction. IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2023: 432-435.

• Yewei Xia, Hao Zhang*, Yixin Ren, Jihong Guan, Shuigeng Zhou. Causal Discovery by Continuous Optimization with Conditional Independence Constraint: Methodology and Performance. IEEE International Conference on Data Mining (ICDM). IEEE, 2023: 668-677.

• Yinghan Hong, Junping Guo, Guizhen Mai, Yingqing Lin, Hao Zhang*, Zhifeng Hao, Gengzhong Zheng. High-dimensional Causal Discovery Based on Heuristic Causal Partitioning. Applied Intelligence (APIN), 2023, 53(20): 23768-23796.

• Hao Zhang, Yewei Xia, Kun Zhang, Shuigeng Zhou, Jihong Guan. Conditional Independence Test Based on Residual Similarity. ACM Transactions on Knowledge Discovery from Data (TKDD), 2023, 17(8): 1-18.

• Yating Zhong, Yuzhong Peng, Yanmei Lin, Dingjia Chen, Hao Zhang, Wen Zheng, Yuanyuan Chen, Changliang Wu. MODILM: Towards Better Complex Diseases Classification Using A Novel Multi-omics Data Integration Learning Model. BMC Medical Informatics and Decision Making (MIDM), 2023, 23(1): 82.

• Yixin Ren, Hao Zhang, Yewei Xia, Jihong Guan, Shuigeng Zhou. Multi-level Wavelet Mapping Correlation for Statistical Dependence Measurement: Methodology and Performance. In: Proceedings of AAAI. 2023, 37(5): 6499-6506.

• Hao Zhang, Yewei Xia, Yixin Ren, Jihong Guan, Shuigeng Zhou. Differentially Private Nonlinear Causal Discovery from Numerical Data. In: Proceedings of AAAI. 2023, 37(10): 12321-12328.

• Jieguang He, Zhiping Peng, Delong Cui, Jingbo Qiu, Qirui Li, Hao Zhang. Enhanced Sooty Tern Optimization Algorithm Using Multiple Search Guidance Strategies and Multiple Position Update Modes for Solving Optimization Problems. Applied Intelligence (APIN), 2023, 53(6): 6763-6799.

• Hao Zhang, Kun Zhang, Shuigeng Zhou, Jihong Guan. Residual Similarity Based Conditional Independence Test and Its Application in Causal Discovery. In: Proceedings of AAAI, 2022, 36(5): 5942-5949.

• Hao Zhang, Shuigeng Zhou, Chuanxu Yan, Jihong Guan, Xin Wang, Ji Zhang, Jun Huan. Learning Causal Structures Based on Divide and Conquer. IEEE Transactions on Cybernetics (TCYB), 2022, 52 (5), 3232-3243.

• Yuzhong Peng, Daoqing Gong, Chuyan Deng, Hongya Li, Hao Zhang*. An Automatic Hyperparameter Optimization DNN Model for Precipitation Prediction. Applied Intelligence (APIN), 2022, 52(3), 2703–2719.

• Hao Zhang, Kun Zhang, Shuigeng Zhou, Jihong Guan. Testing Independence Between Linear Combinations for Causal Discovery. In: Proceedings of AAAI. 2021, 6538-6546.

• Hao Zhang, Chuanxu Yan, Shuigeng Zhou, Jihong Guan, Ji Zhang. Combined Cause Inference: Definition, Model and Performance. Information Sciences (INS). 2021, 574: 431-443.

• Zhihao Li, Haipeng Jia, Yunquan Zhang, Shice Liu, Shigang Li, Xiao Wang, Hao Zhang. Efficient Parallel Optimizations of A High-performance SIFT on GPUs. Journal of Parallel and Distributed Computing (JPDC), 2019, 124: 78-91.

• Hao Zhang, Shuigeng Zhou, Jihong Guan. Measuring Conditional Independence by Independent Residuals for Causal Discovery. ACM Transactions on Intelligent Systems and Technology (TIST). 2019, 10(5):50-69.

• Yuzhong Peng, Huasheng Zhao, Hao Zhang, Wenwei Li, Xiao Qin, Jianping Liao, Zhiping Liu, Jie Li. An extreme Learning Machine and Gene Expression Programming-based Hybrid Model for Daily Precipitation Prediction. International Journal of Computational Intelligence Systems (IJCIS), 2019, 12(2): 1512-1525. 

• Hao Zhang, Shuigeng Zhou, Jihong Guan. Recursively Learning Causal Structures Using Regression-based Conditional Independence Test. In: Proceedings of AAAI. 2019, 3108-3115.

• Hongya Li, Yuzhong Peng, Chuyan Deng, Yonghua Pan, Daoqing Gong, Hao Zhang. Multicellular Gene Expression Programming-based Hybrid Model for Precipitation Prediction Coupled with EMD. International Conference on Intelligent Computing (ICIC), 2018: 207-218.

• Hao Zhang, Shuigeng Zhou, Jihong Guan. Measuring Conditional Independence by Using Independent Residuals: Theoretical Results and Application in Causal Discovery. In: Proceedings of AAAI. 2018, 2029-2036.

• Hao Zhang, Shuigeng Zhou, Kun Zhang, Jihong Guan. Causal Discovery by Using Regression-based Conditional Independence Tests. In: Proceedings of AAAI. 2017, 1250-1256.

• Yifu Huang, Kai Huang, Yang Wang, Hao Zhang, Jihong Guan, Shuigeng Zhou. Exploiting Twitter Moods to Boost Financial Trend Prediction Based on Deep Network Models. Intelligent Computing Methodologies: International Conference on Intelligent Computing (ICIC), 2016: 449-460.

• Zhifeng Hao, Hao Zhang*, Ruichu Cai, Wen Wen, Zhihao Li. Causal Discovery on High Dimensional Data. Applied Intelligence (APIN), 2015, 42: 594-607.

   

国家自然科学基金面上项目，面向多模态生物标志物的因果发现研究，负责人，2025-01--2028-12

国家自然科学基金青年项目，面向癌症数据的因果推断研究及其在致病基因识别的应用，负责人，2021-01--2023-12

国家自然科学基金联合项目，大数据查询处理的隐私保护技术，主要参与，2017-01--2020-12

国家自然科学基金面上项目，基于类不平衡深度特征学习的石化设备故障信号分类研究，主要参与，2022-01--2025-12

国家重点研发计划，面向跨尺度医学数据的融合表征及因果数学理论与应用，课题骨干，2022-12--2027-11

中国科学院战略性先导科技专项，多维大数据驱动的中国人群精准健康研究，课题骨干，2020-01--2024-12

中国博士后面上一等资助项目，基于深度神经网络的高维因果发现方法研究，负责人，2022-10--2023-09

广东省自然科学基金面上项目，面向高维数据的递归式因果发现研究，负责人，2025-01--2027-12

广东省自然科学基金面上项目，基于因果进化算法的大规模黑盒优化问题研究，单位负责人，2022-01--2024-12

广东省自然科学基金面上项目，面向民航空域监视系统的轻量级安全技术研究，主要参与，2021-01--2023-12

广东省高校青年创新人才项目，基于因果独立性测试的致病基因挖掘算法研究，负责人，2021-01--2022-12

广东省普通高校创新团队项目，生物序列与结构大数据智能算法研究创新团队，重要成员，2025-01--2027-12

深圳市博士后留（来）深科研资助项目，负责人，2024-01--2026-12

深圳市基础研究重点项目，面向重症监护的只能生命检测及预警技术研究，重要成员，2025-01--2027-12

上海宝信委托项目，热轧L2系统粗轧宽展和轧制力预测模型研发，负责人，2022-01--2022-12

   

姓名 - 指导阶段 - 现状/去向

陈铭杰     本科、硕士     SIAT科研助理

郭俊平     本科、硕士     在读硕士

陈思达               硕士     在读硕士

赵剑波               硕士     在读硕士

陈志琛               硕士     在读硕士

张俊财               硕士     在读硕士

陈少凡               硕士     在读博士

夏业伟     硕士、博士     在读博士

任一鑫               博士     在读博士

徐雯微               硕士     字节跳动

陈汉儒               硕士     华为上研所