张浩，博士，副研究员，硕士生导师。
张浩先后在广东工业大学，复旦大学，美国卡内基梅隆大学，香港中文大学和中国科学院深圳先进技术研究进行独立性分析，因果推断，生物医学数据分析等方向的学习与研究；主持国家青年，博士后一等资助，广东省教育厅创新人才项目；参与/子课题人参与国家面上，国家联合，广东省面上项目；在CCF 推荐的国际重要学术期刊和会议上发表论文20余篇；担任ICML，NeurIPS，AAAI，ECML-PKDD， TNNLS，TIST，IJIS等程序委员/审稿人。
工作经历：
1. 2023-至今 中国科学院深圳先进技术研究院，生物医学信息研究中心，PI,硕士生导师
2. 2021-2023 复旦大学，计算机系，博士后，合作导师:周水庚
3. 2020-2021 广东石油化工学院，计算机系，副教授
教育经历：
1. 2018/10-2019/10，美国卡内基梅隆大学，机器学习系，导师:Kun Zhang
2. 2015/9-2020/1，复旦大学，理学博士，导师:周水庚
3. 2012/9-2015/7，广东工业大学，数学，理学硕士，导师:郝志峰
4. 2007/9-2011/7，广东工业大学，信息与计算科学，理学学士
科研项目：
1.国家自然科学基金青年项目(主持)，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，2021-2023，结题。
2.中国博士后面上一等资助项目(主持)，基于深度神经网络的高维因果发现方法研究，2022-2023，结题。
3.广东省教育厅高校青年创新人才项目(主持)，基于因果独立性测试的致病基因挖掘算法研究，2021-2022，结题。
4.上海宝信委托项目(主持)，热轧L2系统粗轧宽展和轧制力预测模型研发，2022，结题。
研究成果：
1. Yuzhong Peng*, Hao Zhang*, Ziqiao Zhang, Shuigeng Zhou, and Shaojie Qiao. GEP-DL4Mol: A Novel Molecular Deep-learning Model Optimization Framework for Boosting Molecular Properties Prediction. 24th IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2023)
2. Yewei Xia, Hao Zhang*, Yixin Ren, Jihong Guan, and Shuigeng Zhou*. Causal Discovery by Continuous Optimization with Conditional Independence Constraint: Methodology and Performance. 23rd IEEE International Conference on Data Mining (ICDM 2023)
3. Hao Zhang, Yewei Xia, Kun Zhang, Shuigeng Zhou, and Jihong Guan. Conditional Independence Test Based on Residual Similarity. ACM Transactions on Knowledge Discovery from Data (TKDD 2023)
4. Yinghan Hong, Junping Guo*, Guizhen Mai, Yingqing Lin, Hao Zhang*, Zhifeng Hao, and Gengzhong Zheng. High-dimensional causal discovery based on heuristic causal partitioning. Applied Intelligence (APIN 2023)
5. Hao Zhang, Yewei Xia, Yixin Ren, Jihong Guan, and Shuigeng Zhou. Differentially Private Nonlinear Causal Discovery from Numerical Data. 37th AAAI Conference on Artificial Intelligence (AAAI 2023)
6. Yixin Ren, Hao Zhang, Yewei Xia, Jihong Guan, and Shuigeng Zhou. Multi-level Wavelet Mapping Correlation for Statistical Dependence Measurement: Methodology and Performance. 37th AAAI Conference on Artificial Intelligence (AAAI 2023)
7. Hao Zhang, Chuanxu Yan, Yewei Xia, Jihong Guan, and Shuigeng Zhou. Causal Gene Identification Using Non-linear Regression-based Independence Tests. IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB 2022)
8. Yuzhong Peng*, Daoqing Gong, Chuyan Deng, Hongya Li, Hongguo Cai, and Hao Zhang*. An automatic hyperparameter optimization DNN model for precipitation prediction. Applied Intelligence (APIN 2022)
9. Hao Zhang, Shuigeng Zhou, Chuanxu Yan, Jihong Guan, Xin Wang, Ji Zhang, and Jun (Luke) Huan. Learning Causal Structures Based on Divide and Conquer. IEEE Transactions on Cybernetics (TCYB 2022)
10. Hao Zhang, Chuanxu Yan, Shuigeng Zhou, Jihong Guan, and Ji Zhang.Combined Cause Inference: Definition, Model and Performance. Information Sciences (IS 2022)
11. Hao Zhang, Kun Zhang, Shuigeng Zhou, Jihong Guan, and Ji Zhang. Testing Independence Between Linear Combinations for Causal Discovery. 35th AAAI Conference on Artificial Intelligence (AAAI 2021)
12. Hao Zhang, Shuigeng Zhou, Jihong Guan, and Jun (Luke) Huan. Recursively Learning Causal Structures Using Regression-based Conditional Independence Test. 33th AAAI Conference on Artificial Intelligence (AAAI 2019)
13. Hao Zhang, Shuigeng Zhou, Jihong Guan, and Jun (Luke) Huan. Measuring Conditional Independence by Independent Residuals for Causal Discovery. ACM Transactions on Intelligent Systems and Technology (TIST 2019)
14. Hao Zhang, Shuigeng Zhou, and Jihong Guan. Measuring Conditional Independence by Using Independent Residuals: Theoretical Results and Application in Causal Discovery. 32th AAAI Conference on Artificial Intelligence (AAAI 2018)
15. Hao Zhang, Shuigeng Zhou, Kun Zhang, and Jihong Guan. Causal Discovery by Using Regression-based Conditional Independence Tests. 31th AAAI Conference on Artificial Intelligence (AAAI 2017)
联系方式：h.zhang10@siat.ac.cn
