Yanxia Zhang 

National Astronomical Observatory          
Chinese Academy of Sciences                    
Datun Road 20A, Chaoyang District
Beijing 100012, China

Tel:  (8610)64841693 
FAX: (8610)64878240

Research Areas

● Machine Learning and Artificial Intelligence in Astronomy

● Photometric Redshift Measurement of Galaxies and Quasars

● Time Series Analysis in Astronomy

● Multiwavelength Astronomy


1. B.A.: Hebei Normal University, Shijiazhuang, Hebei Province (1997).
    Major: Physics.

2. M.S.: Hebei Normal University, Shijiazhuang, Hebei Province (2000).
    Major: Astrophysics.

3. Ph.D.: National Astronomical Observatories, CAS, Beijing (2003).
    Major: Astrophysics.
Work Experience
1. 2013-pres. Professor, National Astronomical Observatories, 
     Chinese  Academy of Sciences, Beijing

2. 2006-2013. Associate Professor, National Astronomical
    Observatories, Chinese Academy of Sciences, Beijing
3. 2003-2005. Assistant Professor, National Astronomical
    Observatories, Chinese Academy of Sciences, Beijing 


Changhua Li, Yanxia Zhang, Chenzhou Cui, Dongwei Fan, Yongheng Zhao, Xuebing Wu, Jing-Yi Zhang, Yihan Tao, Jun Han, Yunfei Xu, Shanshan Li, Linying Mi, Boliang He, Zihan Kang, Youfen Wang, Hanxi Yang, Sisi Yang, Photometric Redshift Estimation of Galaxies in the DESI Legacy Imaging Surveys, 2023, MNRAS, 518, 513–525

Changhua Li, Yanxia Zhang, Chenzhou Cui, Dongwei Fan, Yongheng Zhao, Xuebing Wu, Jing-yi Zhang, Jun Han, Yunfei Xu, Yihan Tao, Shanshan Li, Boliang He, Photometric redshift estimation of BASS DR3 quasars by machine learning, 2022, MNRAS, 509, 2289-2303

Zhang Zhen, Jiang Bin, Zhang Yanxia, Automatic Detection and Classification of Radio Galaxy Images by Deep Learning, 2022, PASP, 134, 064503

Kun Li, Ce Yu, Yanxia Zhang, Chao Sun, Jian Xiao, Chenzhou Cui, Yajie Zhang, Yifei Mu, TSCat: data model and storage engine for AI-based light-curve analysis, 2022, MNRAS, 514, 4756–4764

Zhang Yanxia, Zhao Yongheng, Wu Xue-Bing, Classification of 4XMM-DR9 sources by machine learning, 2021, MNRAS, 503, 5263–5273

Li Changhua, Zhang Yanxia, Cui Chenzhou, Fan Dongwei, Zhao Yongheng, Wu Xue-Bing, He Boliang, Xu Yunfei, Li Shanshan, Han Jun, Tao Yihan, Mi Linying, Yang Hanxi, Yang SisiIdentification of BASS DR3 sources as stars, galaxies, and quasars by XGBoost, 2021, MNRAS, 506(2), 1651–1664

Yu Ce, Li Kun, Zhang Yanxia, Xiao Jian, Cui Chenzhou, Tao Yihan, Tang Shanjiang, Sun Chao, Bi Chongke,A survey on machine learning based light curve analysis for variable astronomical sources, 2021, WIREs Data Mining and Knowledge Discovery, 11(5), e1425

Zhang, Jingyi, Zhang ,Yanxia, Zhao, Yongheng, RR Lyrae Star Candidates from SDSS Databases by Cost-sensitive Random Forests,2020, ApJS, 246: 8

Jin, Xin, Zhang,Yanxia, Zhang,Jingyi, Zhao,Yongheng, Wu,Xue-bing, Fan, Dongwei, Efficient selection of quasar candidates based on optical and infrared photometric data using machine learning, 2019, Monthly Notices of the Royal Astronomical Society, 484: 4539-4549

Zhang, Jingyi, Zhang ,Yanxia, Zhao, Yongheng, Imbalanced learning for RR Lyrae stars based on SDSS and GALEX databases, 2018, AJ, 155: 108

Zhang, Y., Zhao, Y., Astronomy in the Big Data Era, Data Science Journal, 2015, 14(11), pp.1-9 

Zhang,Yan-xia, Zhou, Xin-lin, Zhao, Yong-heng, Wu, Xue-bing, Statistical Study of 2XMMi-DR3/SDSS-DR8 Cross-correlation Sample, 2013, AJ, 145, 42-54 

Peng Nanbo,Zhang Yanxia and Zhao Yongheng, A SVM-kNN Method for Quasar-Star Classification, 2013, Science in China G: Physics and Astronomy, 56(6), 1-8

Zhang Yanxia, Ma He, Peng Nanbo, Zhao Yongheng, Wu Xue-bing, Estimating Photometric Redshifts of Quasars via K-nearest Neighbors Approach Based on Large Survey Databases, 2013,  AJ, 146, 22-31

Han, Bo; Ding, Hong-Peng; Zhang, Yan-Xia; Zhao, Yong-Heng, Photometric redshift estimation for quasars by integration of KNN and SVM, Research in Astronomy and Astrophysics, 2016,Volume 16, Issue 5, 74,10pp   

Zhang,Yan-xia, Zhou, Xin-lin, Zhao, Yong-heng, Wu, Xue-bing, Statistical Study of 2XMMi-DR3/SDSS-DR8 Cross-correlation Sample, 2013, AJ, 145,4 

Zhang,Yanxia, Zhao, Yongheng, Zheng, Hongwen, Wu, Xue-bing, Classification of Quasars and Stars by Supervised and Unsupervised Methods, 2013, Proceedings IAU Symposium 288, 333  

Yuan, Hailong; Zhang, Haotong; Zhang, Yanxia; Lei, Yajuan; Dong, Yiqiao; Zhao, Yongheng, ASERA: A spectrum eye recognition assistant for quasar spectra, 2013,Astronomy and Computing, Volume 3, p. 65-69
Zhang, Yanxia, Li, Lili, Zhao, Yongheng, Morphology Classification and Photometric Redshift Measurement of Galaxies, 2009, MNRAS, 392,233-239 
Zhang, Yanxia, & Zhao, Yongheng. Automated clustering algorithms for classification of astronomical objects, 2004, A&A, 422, 1113-1121 
Zhang, Yanxia. Research on Automatic Classification Methods in Multiwavelength Astrophysics, 2004, PASP, 116, 184 
Zhang, Yanxia, & Zhao, Yongheng. Classification in Multidimensional Parameter Space: Methods and Examples, 2003, PASP, 115, 1006-1018 
Zhang, Yan-xia, & Zhao, Yong-heng. Learning Vector Quantization for Astronomical Objects Classification, 2003, ChJAA, 3, 183 
Zhang, Yanxia, Zhao, Yongheng, A Comparison of BBN, ADTree and MLP in separating Quasars from Large Survey Catalogues,2007, ChJAA, 7, 289-296
Zhang, Yanxia, Zhao,Yongheng,Gao,Dan, Decision table for classifying point sources based on FIRST and 2MASS databases,2008, Advances in Space Research, Volume 41, Issue 12, p. 1949-195 
Gao, Dan, Zhang,Yanxia, Zhao,Yongheng, Random forest algorithm for classification of multiwavelength data, 2009, RAA,9, 220-226
Gao, Dan, Zhang, Yanxia, Zhao,Yongheng, Support vector machines and kd-tree for separating quasars from large survey data bases,2008,MNRAS, 386(3), pp. 1417-1425 
Wang, Dan, Zhang, Yanxia, Liu, Chao, Zhao, Yongheng, Two Novel Approaches for Photometric Redshift Estimation based on SDSS and 2MASS, 2008, ChJAA, 8(1), pp. 119-126 
Zhao, Yongheng, Zhang, Yanxia, Comparison of decision tree methods for finding active objects, 2008, Advances in Space Research, Volume 41, Issue 12, p. 1955-1959 
Zheng, Hongwen, Zhang, Yanxia, Feature selection for high-dimensional data in astronomy, 2008,  Advances in Space Research, Volume 41, Issue 12, p. 1960-1964 
Wang Dan, Zhang, Yan-Xia et al., 2007, Kernel Regression For Determining Photometric Redshifts From Sloan Broadband Photometry, MNRAS, 382, 1601 -1606
Li, Lili, Zhang, Yanxia, Zhao, Yongheng, Yang, Dawei, Estimating Photometric Redshifts with Artificial Neural Networks and Multi-parameters, 2007, ChJAA, 7, 448 
Yan, Taisheng; Zhang, Yanxia; Zhao, Yongheng; Li, Ji, Exploration of SDSS stellar database by AutoClass, Science in China Series G, 2011, Vol. 54 (9): 1717-1726 
Li, Lili, Zhang,Yanxia,Zhao,Yongheng,k-nearest neighbors for automated classification of celestial objects, 2008, Science in China, Series G,51(7), 916-922 



裴彤  硕士研究生  070420-天文技术与方法  

彭南博  博士研究生  070420-天文技术与方法  

张静怡  博士研究生  0704Z1-天文技术与方法  

金鑫  硕士研究生  070401-天体物理  


李长华  博士研究生  0704Z1-天文技术与方法