Personal Information
Name: Zhangang WANG
Title: Associate Professor
E-mail: millwzg@163.com
Research Interests
(1) New method (Machine learning) for complex 3D Geological Modeling and Structural Analysis in Coal Mines、Geological Survey and Oil& Gas Expoloration.
(2) High Performance Spatial Data Computing and Industrial Software Development
Education/Work Background
1999.09-2003.07，School of Earth and Space Science, Peking University, Bachelor;
2003.09-2008.07，School of Earth and Space Science, Peking University, PhD;
2008.07-2010.07，College of Geoscience and Survey Engineering, China University of Mining Technology,Beijing, Postdoc；
2010.07-2017.07，College of Geoscience and Survey Engineering, China University of Mining Technology,Beijing, Assistant Professor；
2017.08-Now，College of Geoscience and Survey Engineering, China University of Mining Technology,Beijing, Associate Professor；
2018.11-2019.11，University of Illinois Urbana-Champaign, Visitor Scholar；
Teaching Courses
Geophyical Inversion method
Structural Geology
Computer Graphics
Mathematical Geoscience
Key Research Funding
[1]Research on key technologies of ultra-large-scale geological spatiotemporal big data model and distributed computing. National Natural Science Foundation of China (No. U2344216) 2024-2027
[2] Formal representation and standardization of 3D geological structural model. National Natural Science Foundation of China (No. 41672326) 2017-2020
Honors
2023.11, I was awarded the title of 2022-2023 Excellent Instructor of China University of Mining Technology,Beijing.
Selected Publications (* denotes Corresponding author)
[1] Zhangang Wang, Zixing Wu, Honggang Qu & Xianghong Wang. Boolean matrix operators for computing binary topological relations between complex regions, International Journal of Geographical Information Science, 2019
[2] Zhangang Wang, Honggang Qu, Zixing Wu. Geo3DML: A standard-based exchange format for 3D geological models .Computers & Geosciences, 2017.
[3] Zhangang Wang,Honggang Qu. Formal representation of 3D structural geological models. Computers & Geosciences, 2016.