Dr. Chengbin Wang is an associate professor of School of Earth Resources at the China University of Geosciences (Wuhan). He received his PhD degree of Mineral Prospecting and Exploration from China University of Geosciences in Dec. 2017.   

His research focues on Integration and Interoperability of Non-structured Geological Big Data, GIS-based Mineral Predication via Machine Learning, Construction and Application of Mineral Deposits Knowledge Graph, and LLM and Agent in the Geoscience.

Professional Appointment

07/2018-    Associate Professor (Special), China University of Geosciences (Wuhan)

Recent Honors, Awards & Scholarship

10/2023 Ministry of Natural Resources High-level Science and Technology Innovation Talent Project

10/2017  Best paper award, Conference on Annual Meeting of Geological Society of China

09/2017  C&G Research Scholarship, International Association of Mathematical Geosciences

05/2017  USGS Travel Grants

Funded Project

PI

10/2024-10/2027, Program Research on deep earth big data analysis model

06/2024/05/2026, Construction of knowledge graph of Geology and mineral deposit and AIGC intelligent geoscience information service in Ningxia

04/2024-04/2026 Accurate and intelligent prediction and evaluation of Hunan gold mines driven by geological big data

09/2017~09/2017 IAMG, Text Information Extraction and Knowledge Graph Construction from Geoscience Literature, $ 2,500.

12/2012~06/2014, Chinese Academy of Geological Sciences, Application of Hilbert-Huang and Independent Component Analysis on the Extraction of Metallogenic Information, ¥50,000.

Project Participant

06/2017-   National Key Research and Development Program, 3D geophysical modeling and Mineral Prediction in the deep of Earth Crust, ¥ 4,820,000.

01/2015-   Ministry of Land and Resources, Automatic Indexing and Summarization Research of Geological Report, ¥ 350,000.

03/2013~05/2014 Industry Project, Gold Mineralization and Mineral Predication in the Dahaoshan-Lishan Area, Jiangxi Province, ¥ 400,000.

01/2013~12/2015 China Geological Survey, Geophysical Exploration and Remote Sensing in the Concealed Areas, ¥ 2,500,000.

Publication (Selected)

Fu Y., Wang M., Wang C.^*, Dong S., Chen J., Wang J., Yu H., Huang J., Chang L., and Wang B., 2025.GeoMinLM: A Large Language Model in Geology and Mineral Survey in Yunnan Province. Ore Geology Reviews, Online

Wang C.*, Tan L., Li Y., Wang M., Ma X., and Chen J., 2024. Ontology-driven Relational Data Mapping for Constructing a Knowledge Graph of Porphyry Copper Deposits. Earth Science Informatics .17(3):2649-2660 https://doi.org/10.1007/s12145-024-01307-5.

Wang C.*, Li Y., Chen J. and Ma X., 2023. Named Entity Annotation Schema for Geological Literature Mining in the Domain of Porphyry Copper Deposits. Ore Geology Reviews.152:105243. https://doi.org/10.1016/j.oregeorev.2022.105243

Wang C.*, Li Y., Chen J. 2023.Text Mining and Knowledge Graph Construction from Geoscience Literature Legacy: A Review. In: Ma X, Mookerjee M, Hsu L, Hills D (eds) Recent Advancement in Geoinformatics and Data Science, GSA Special paper. https://doi.org/10.1130/2022.2558(02)

Wang C.*, Zhao K-D.*, Chen J. and Ma X., 2022. Examining Fingerprint Trace Elements in Cassiterite: Implications for Primary Tin Deposit Exploration. Ore Geology Reviews. 149. 105082. https://doi.org/10.1016/j.oregeorev.2022.105082

Ma C., Morrision S., Muscente D., Wang C., and Ma X., 2022. Incorporate temporal topology in a deep-time knowledge base to facilitate data-driven discovery in geoscience. Geoscience Data Journal. https://doi.org/10.1002/gdj3.171

（Yang X., Chen J., Wang C., and Chen Z., 2022. Residual Dense Autoencoder Network for Nonlinear Hyperspectral Unmixing.  IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. https://ieeexplore.ieee.org/document/9815532

Wang C.*, Chen J.*, and Ouyang Y., 2022. Determination of Predictive Variables in Mineral Prospectivity Mapping Using Supervised and Unsupervised Methods. Natural Resouces Research.31, 2081–2102. https://doi.org/10.1007/s11053-021-09982-7

（Wang C., Ma X., 2021,  Digital Geological Mapping. In: Daya Sagar B., Cheng Q., McKinley J., Agterberg F. (eds) Encyclopedia of Mathematical Geosciences. Encyclopedia of Earth Sciences Series. Springer, Cham. https://doi.org/10.1007/978-3-030-26050-7_88-1

（Wang C., Ma X., 2021, Text Mining. In: Daya Sagar B., Cheng Q., McKinley J., Agterberg F. (eds) Encyclopedia of Mathematical Geosciences. Encyclopedia of Earth Sciences Series. Springer, Cham. https://doi.org/10.1007/978-3-030-26050-7_325-1

Wang, C.*; Wang, X.; Chen, J., 2021. Digital Geological Mapping to Facilitate Field Data Collection, Integration, and Map Production in Zhoukoudian, China. Applied Sciences. 11, 5041. https://doi.org/10.3390/app11115041

Ma, X., Ma, C., and Wang, C., 2020. A new structure for representing and tracking version information in a deep time knowledge graph.Computer and Geosciences, DOI:10.1016/j.cageo.2020.104620 【PDF】

Wang, C.*, Pan, Y., Chen, J.*, et al., 2020. Indicator Element Selection and Geochemical Anomaly Mapping Using Recursive Feature Elimination and Random Forest Methods in the Jingdezhen Region of Jiangxi Province, South China, Applied Geochemistry, 122,104760. DOI:10.1016/j.apgeochem.2020.104760【PDF】

Wang, C. and Ma, X., 2019.Text Mining to Facilitate Domain Knowledge Discovery. In: Abdelkrim El Mouatasim (ed.),Text Mining - Analysis, Programming and Application. DOI：10.5772/intechopen.85362【PDF】

Wang, C., Ma, X., Chen, J., 2018. Ontology-Driven Data Integration and Visualization for Exploring Regional Geologic Time and Paleontological Information, Computer & Geosciences. 115:12-19 DOI: 10.1016/j.cageo.2018.03.004.

Wang C., Chen J., 2018. Identification of concealed geological structures in a Grassland Area in Inner Mongolia, China: A Perspective from Temperature Vegetation Dryness Index (TVDI).

Wang, C., Ma, X., Chen, J. and, Chen J., 2018. Information Extraction and Knowledge Graph Construction from Geoscience Literature, Computer & Geosciences.112：112-120 DOI: 10.1016/j.cageo.2017.12.007

Wang, C., Ma, X. and Chen, J., 2018. The application of data pre-processing technology in the geoscience big data. Acta Petrologica Sinica, 34(2): 303-313(in Chinese with English abstract)

Ma, X., Hummer, D., Golden, J., Fox P., Hazen, R., Shaunna, M., Downs, R., Madhikarmi, B., Wang, C., Mayer M., 2017. Using visualized exploratory data analysis to facilitate collaboration and hypothesis generation in cross-disciplinary research, ISPRS International Journal of Geo-Information 6(11): 368-378.

 Wang, C., Chen, J., Xiao, F., Tounkara, F. and Li, L.,2016. Radioelement distributions and analysis of microtopographical influences in a shallow covered area, Inner Mongolia, China: Implications for mineral exploration, Journal of Applied Geophysics.133:62-69 DOI: 10.1016/j.jappgeo.2016. 06.013.

Wang, C., Rao, J., Chen, J., Ouyang, Y., Qi, S. and Li, Q., 2016. Prospectivity Mapping for “Zhuxi type” Hydrothermal Cu-W Polymetallic Deposits in the Jingdezhen Region of Jiangxi Province, South China, Ore Geology Reviews.89:1-14 DOI: 10.1016/j.oregeorev.2017.05.022.

Xiao, F., Chen, J., Agterberg F., Wang, C., 2014. Element behavior analysis and its implications for geochemical anomaly identification: A case study for porphyry Cu–Mo deposits in Eastern Tianshan, China. Journal of Geochemical Exploration, 145: 1-11.

Xiao，F., Chen, J., Zhang, J., Wang, C., Wu, G., Agterberg, FP. 2012.Singularity mapping and spatially weighted principal component analysis to identify geochemical anomalies associated with Ag and Pb-Zn polymetallic mineralization in Northwest Zhejiang, China. Journal of Geochemical Exploration,122:90-100.