Personal Information
Name: Na Xu
Title: Professor; PHD supervisor
E-mail: xuna1011@gmail.com; xuna@cumtb.edu.cn
Research Interests
Big data;
Machine learning;
Deep learning;
Coal;
Geosciences;
Artificial intelligengce
Education/Work Background
Shandong University, Master;
China University of Mining and Technology (Beijing), PhD;
China University of Mining and Technology (Beijing), Professor.
Teaching Courses
Principles and Applications of the Database;
Object-oriented Programming;
Geoscience Big Data and Cloud Computing;
Geoscience Software Development;
Machine Learning Applications in Geophysics;
Mathematical Geosciences;
Key Research Funding
1. Na Xu. Research on topology discovery and its theory of supply chain information system. National Natural Science Foundation of China (No. 61202363), PI
2. Na Xu. Spatial data service composition model and its quality of service in cloud computing. National Natural Science Foundation of China (No. 61772320), PI
3. Na Xu. Toward the source and modes of occurrence of elements in coal through big data. National Natural Science Foundation of China (No. 42372191), PI
4. Na Xu. Toward the intelligent model of strategic metal resources in coal-bearing strata through big data. National Key Research and Development Program of China (No. 2021YFC2902005), PI
Honors
1. Awarded the Second Prize for Excellent Teaching Quality at China University of Mining and Technology (Beijing) in 2022.
2. Awarded the Second Prize of the Science and Technology Award by the China National Coal Association in 2018.
3. Awarded the First Prize of Science and Technology Progress Award of Shandong Province in 2011.
4. Awarded the Best Oral Presentation at the 9th International Workshop on Compositional Data Analysis (CoDaWork 2022) in 2022.
5. Awarded the Contribution Award at IEEE ICAL International Conference in 2008 and 2009.
6. Guided students in the 17th China post-graduate mathematical contest in modeling and awarded the National Second Prize.
7. Guided students in the 18th China post-graduate mathematical contest in modeling and awarded the National Third Prize.
8.Awarded the "Outstanding instructor award" in the National College Students' Network Business Innovation Application Contest organized by the Internet Society of China in 2007.
9. Awarded Outstanding Class Teacher in 2021.
Selected Publications (* denotes Corresponding author)
1. Xu, N., et al., 2022. Toward the Threshold of Radiation Hazards of U in Chinese Coal through the CART Algorithm. Environ Sci Technol. 56, 1864-1874. https://doi.org/10.1021/acs.est.1c07776. (SCI, Q1)
2. Xu, N., et al., 2020. What do coal geochemistry statistics really mean? Fuel. 267, 117084. https://doi.org/10.1016/j.fuel.2020.117084. (SCI, Q1)
3. Xu, N., et al., 2022. Coal elemental (compositional) data analysis with hierarchical clustering algorithms. Int. J. Coal Geol. 249, 103892. https://doi.org/10.1016/j.coal.2021.103892. (SCI, Q1)
4. Xu, N., et al., 2023. Prediction of higher heating value of coal based on gradient boosting regression tree model. Int. J. Coal Geol. 274, 104293. https://doi.org/10.1016/j.coal.2023.104293. (SCI, Q1)
5. Xu, N., et al., 2023. Application of self-organizing maps to coal elemental data. Int. J. Coal Geol. 277, 104358. https://doi.org/10.1016/j.coal.2023.104358. (SCI, Q1)
6. Xu, N., et al., 2023. Modes of occurrence of elements in high-germanium coals using correlation analysis algorithm. Appl. Geochem. 152, 105647. https://doi.org/10.1016/j.apgeochem.2023.105647. (SCI, Q2)
7. Xu, N., et al., 2023. Crack-Att Net: crack detection based on improved U-Net with parallel attention. Multimedia Tools and Applications. https://doi.org/10.1007/s11042-023-15201-7. (SCI, Q2)
8. Xu, N., et al., 2021. Average Linkage Hierarchical Clustering Algorithm for Determining the Relationships between Elements in Coal. ACS Omega. 6, 6206-6217. https://doi.org/10.1021/acsomega.0c05758. (SCI, Q2)
9. Xu, N., et al., 2020. Towards Consistent Interpretations of Coal Geochemistry Data on Whole-Coal versus Ash Bases through Machine Learning. Minerals. 10, 328. https://doi.org/10.3390/min10040328. (SCI, Q2)
10. Xu, N., et al., 2019. Threshold Value Determination Using Machine Learning Algorithms for Ba Interference with Eu in Coal and Coal Combustion Products by ICP-MS. Minerals. 9, 259. https://doi.org/10.3390/min9050259. (SCI, Q2)
11. Xu, N., et al., 2023. Interpretation of coal compositional data on whole-coal versus ash bases through the Weighted Symmetric Pivot Coordinates method, Statistics and Operations Research Transactions. (SCI, Q2)
12. Xu, N., et al., 2023. Advocating the use of Bayesian network in analyzing the modes of occurrence of elements in coal, ACS Omega. (SCI, Q2)
13. Xu, N, et al. 2017.Verifying soundness of geodata web service composition based on Petri nets, Journal of Web Engineering. (SCI, Q4)
14. Xu, N., Huang, B., Li, Q., 2022. Towards the study on the geochemistry through machine learning, Journal of China Coal Society,47,1895-1902.
15. Xu, N., Wang, R., 2023. Interpretation of coal compositional data on whole-coal versus ash bases through the Weighted Symmetric Pivot Coordinates method. CoDa Work.
16. Xu, N., Wang, Q., 2023. Towards the identification of coal macerals through deep learning. The Society of Organic Petrology.