个人简介：

张智强，男，工学博士，副教授。2022年6月毕业于中国地质大学（北京），主持国家级和省部级项目4项。以第一作者身份发表国际SCI和中文核心论文15篇，含中国科学院TOP及行业顶级论文3篇，以第一发明人身份获批专利1项。担任国际数学地质学会会刊《Computers & Geosciences》《Mathematical Geosciences》和《Natural Resources Research》等SCI期刊审稿人。

一、主要研究方向

1. 三维地质建模与矿产资源智能预测

面向国家“深地”战略，基于多模态地学大数据，运用浅层机器学习和深度学习方法，结合空间分析与计算模拟技术，开展矿集区—矿田—矿床—矿体多尺度多参数三维地质建模与矿产资源智能预测，助力深部找矿。

2. 地学大数据挖掘及极端地质事件预测

运用浅层机器学习和深度学习方法，结合奇异性理论，挖掘地学数据深层次特征，并据此开展大规模成矿效应和矿物演化的定量表征、模拟及预测研究。

二、主要科研成果

1、国家自然科学基金青年项目（项目编号：42402301），国家级，基于深度学习的三维成矿预测不确定性评价，主持，在研

2、中华人民共和国科学技术部深地国家科技重大专项子课题（项目编号：2024ZD1001905），国家级，顾及勘查全过程的实时四维成矿预测方法体系研发，主持，在研

3、河北省自然科学基金青年项目（项目编号：D2023403051），省部级，基于深度无监督域自适应方法的三维成矿预测研究—以河北大庙钒钛磁铁矿田为例，主持，在研

4、河北省燕赵黄金台聚才计划骨干人才项目（项目编号：D2023403051），省部级，数据分布偏移背景下基于深度迁移学习的三维成矿预测方法研究，主持，在研

5、河南省文物考古研究院河南省叶县余庄遗址地下空间三维建模项目，主持，在研

三、代表性论文及著作

1. Zhang, Z., Chen, W., Carranza, E.J.M. Han, W., Liu X., Li, Y., Zhang, J., Li, F., Lu, Z., Su, Y., Wang , G. Deep Subdomain Adaptation Network for Three-Dimensional Mineral Prospectivity Modeling with Imbalanced Data: A Case Study of the Damiao–Hongshila Fe–V–Ti Belt, China. Natural Resource Research. 2025. https://doi.org/1 0.1007/s11053-025-10544-4

2. Zhang, Z., Wang, G., Carranza, E.J.M., Li, W., Li Y., Tang, L., Liu, X. Three-dimensional mineral prospectivity mapping using a residual convolutional neural network with lightweight attention mechanisms. Ore Geology Reviews. 2025. https:// do i.org/10.1016/j.oregeorev.2025.106797

3. Zhang, Z., Wang, G., Carranza, E.J.M., Li, Y., Liu, X., Peng, W., Fan, J., Xu, F. Mapping of Gold Prospectivity in the Qingchengzi Pb–Zn–Ag–Au Polymetallic District, China, with Ensemble Learning Algorithms. Natural Resources Research. 2024. https://doi.org/10.1007/s11053-024-10424-3

4. Zhang, Z., Wang, G., Carranza, E.J.M., Du, J., Li, Y., Liu, X., Su, Y. An Uncertainty-Quantification Machine Learning Framework for Data-Driven Three-Dimensional Mineral Prospectivity Mapping. Natural Resources Research. 2024, 33, 1393–1411.

5. Zhang Z., Wang G., Carranza E J M., Liu C., Li J., Fu C., Liu X., Chen C., Fan J., Dong Y. An integrated machine learning framework with uncertainty quantification for three-dimensional lithological modeling from multi-source geophysical data and drilling data. Engineering Geology. 2023, 324: 107255.

6. Zhang Z., Li Y., Wang G., Carranza E J M., Yang S., Sha D., Fan J., Zhang X., Dong Y. Supervised Mineral Prospectivity Map via Class-Balanced Focal Loss Function on Imbalanced Geoscience Datasets. Mathematical Geosciences. 2023, 55, 989–1010.

7. Zhang, Z., Wang, G., Carranza, E.J.M., Fan, J., Liu, X., Zhang, X., Dong, Y., Chang, X., Sha, D. An Integrated Framework for Data-Driven Mineral Prospectivity Mapping Using Bagging-Based Positive-Unlabeled Learning and Bayesian Cost-Sensitive Logistic Regression. Natural Resources Research. 2022. 31, 3041–3060.

8. Zhang, Z., Wang, G., Carranza, E.J.M. Yang, S., Zhao, K., Yang, W., Sha, D. Three-Dimensional Pseudo-Lithologic Modeling Via Adaptive Feature Weighted k-Means Algorithm from Multi-Source Geophysical Datasets, Qingchengzi Pb–Zn–Ag–Au District, China. Natural Resources Research. 2021, 31, 2163–2179

9. Zhang, Z., Wang, G., Cheng, L., Liu, Chong. Bagging-based positive-unlabeled learning algorithm with Bayesian hyperparameter optimization for three-dimensional mineral potential mapping. Computers & Geosciences, 2021, 154, 104817

10. Zhang, Z., Wang, G., Ding, Y., Carranza, E.J.M. 3D mineral exploration targeting with multi-dimensional geoscience datasets, Tongling Cu(-Au) District, China. Journal of Geochemical Exploration. 2021, 221, 106702

11. Zhang, Z., Zhang, J., Wang, G., Carranza, E.J.M., Pang, Z., Wang, H. From 2D to 3D Modeling of Mineral Prospectivity Using Multi-Source Geoscience Datasets, Wulong Gold District, China. Natural Resources Research. 2020, 29, 345–364.

12. Zhang, Z., Wang, G., Ma, Z., Carranza, E.J.M., Jia, W., Du, J., Tao, G., Deng, Z. Batholith-stock scale exploration targeting based on multi-source geological and geophysical datasets in the Luanchuan Mo polymetallic district, China. Ore Geology Reviews. 2019, 118, 103225.

13. Zhang, Z., Wang, G., Carranza, E.J.M., Zhang, J., Tao, G., Zeng, Q., Sha, D., Li, D., Shen, J., Pang, Z. Metallogenic model of the Wulong gold district, China, and associated assessment of exploration criteria based on multi-scale geoscience datasets. Ore Geology Reviews. 2019, 114, 103138.

14. Zhang, Z., Wang, G., Ma, Z., Gong, X. Interactive 3D Modeling by Integration of Geoscience Datasets for Exploration Targeting in Luanchuan Mo Polymetallic District, China. Natural Resources Research. 2018, 27(3), 315-346.

15. 张智强., 王功文., 沙德铭., 曾庆栋., 邱海成．基于深度学习的辽东半岛五龙金矿集区三维矿产资源定量预测．地学前缘. https://doi.org/10.13745/j.esf.sf.20 25.4.50

16. 王功文, 张智强, 李瑞喜, 李俊建, 沙德铭, 曾庆栋, 庞振山, 李大鹏, 黄蕾蕾, 华北重点矿集区大数据三维/四维建模与深层次集成的资源预测评价,  中国科学: 地球科学. 2021, 51(9), 1594-1610.

四、联系方式

Email：zq_zhang_geo@126.com

欢迎对大数据、人工智能和地学多学科交叉感兴趣的本科生报考。