张浩 中国科学院深圳先进技术研究院 副研究员
电子邮件： h.zhang10@siat.ac.cn
通信地址： 深圳市南山区西丽深圳大学城学苑大道1068号
简介
课题组负责人 张 浩，复旦大学-美国卡内基梅隆大学联合培养博士毕业，现为中国科学院深圳先进技术研究院副研究员，中国科学院重点人才备案，深圳市“鹏城孔雀计划”特聘；主要从事因果学习+可解释AI+医学数据分析研究，以第一作者/通讯作者在人工智能+生物信息学领域的国际重要期刊/会议上发表一系列论文，包括 ACM/IEEE TPAMI、TMM、TCYB、TKDD、TIST、TCBB、NeurIPS、KDD、AISTATS、AAAI、ICDM、BIBM、APIN、INS、KBS、AIIM、Briefings in Bioinformatics；担任 AAAI、ICML、ECML-PKDD、TNNLS、TIST、EAAI、ESWA、INS、SEC、IJIS、CIBM、eLife、计算机学报等程序委员会委员/审稿人，JCR-Q1期刊 Interdisciplinary Sciences: Computational Life Sciences 青年编委；主持国家自然科学基金面上、青年，博士后基金一等资助，广东省高校青年创新人才，广东省自然科学基金等项目；课题骨干身份参与中国科学院战略性先导科技专项、国家重点研发计划、国家联合基金、深圳市重点基金等项目。
课题组以培养学生科研能力为主，2024年学生以第一作者发表高水平学术论文（CCF-A类 > ACM/IEEE Trans > SCI一区）8 篇，获广东省计算机学会优秀论文一等奖、三等奖两项。
欢迎对因果学习+可解释AI+医学数据分析感兴趣的同学加入我们课题组，中国科学院大学、南方科技大学、深圳理工大学硕士生每年都有名额，或其他学校的客座访问硕士/博士生，也欢迎博士后加入。
论文发表（* Corresponding Author）
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.
Wen Zheng, Zhongji Li1, Yuanyuan Chen, Lei Deng, Hao Zhang, Yuzhong Peng. GEP-DNN4Mol: Automatic Chemical Molecular Design Based on Deep Neural Networks and Gene Expression Programming. Health Information Science and Systems, 2025, 13(31), https://doi.org/10.1007/s13755-025-00344-8.
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, 37: 99800-99835.
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, 46(12): 10259-10271.
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), 2024, 27: 1086-1099.
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), 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), 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), 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.
科研项目