● 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.

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 

Wu Jingjing, He Yuchen, Wan Wenyu, Qu Meixia, Jiang Bin, ZhangYanxia，Classification of Astronomical Spectra Based on Multiscale Partial Convolution, 2024, AJ，167:260 (19pp)

 

Zeraatgari Fatemeh Zahra, Hafezianzade Fatemeh, Zhang Yanxia, Mei Liquan, Ayubinia Ashraf, Mosallanezhad Amin, and Zhang Jingyi, Machine learning-based photometric classification of galaxies, quasars, emission-line galaxies, and stars，2024, MNRAS, 527（3）, January 2024, Pages 4677–4689

 

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

 

Zhang Jingyi, Zhang Yanxia, Kang Zihan, Li Changhua, Zhao Yongheng, A Catalog of Young Stellar Objects from the LAMOST and ZTF Surveys, 2023, ApJSS, 267, 7

 

Zhang Jingyi, Zhang Yanxia, Kang Zihan, Li Changhua, Tao Yihan, Zhao Yongheng, Wu Xue-Bing, A novel approach for variable star classification based on imbalanced learning, 2023, PASA, 40, e037

 

Wang Mengxin, Wu Jingjing, Jiang Bin, Zhang Yanxia, Searching for Galactic HII Regions from the LAMOST Database Based on the Multihead WDCNN Model, 2023, ApJSS, 267:39

 

Wei Jiaqi, Jiang Bin, Zhang Yanxia, Identification of Blue Horizontal Branch Stars with Multimodal Fusion, 2023, PASP, 135:084501

 

Huang Junfeng, Qu Meixia, Jiang Bin, Zhang Yanxia, Automatic detection of cataclysmic variables from SDSS images, 2023, PASA,40, e033

 

He Yin, Zhang Yanxia, Chen Shuxin, Hu Yu, Facial Expression Recognition Using Hierarchical Features With Three-Channel Convolutional Neural Network, 2023, IEEE Access, 11, 84785-84794

 

Kang Zihan, Zhang Yanxia, Zhang Jingyi, Li Changhua, Kong Minzhi, Zhao Yongheng, Wu Xue-Bing, Periodic variable star classification with deep learning: handling data imbalance in an ensemble augmentation way, 2023, PASP, 135, 094501 (10pp)

 

He Yuchen, Wu Jingjing, Wang Wenyu, Jiang Bin, Zhang Yanxia, AstroYOLO: A hybrid CNN–Transformer deep-learning object-detection model for blue horizontal-branch stars, 2023, PASJ, 00(0), 1-13

 

Wu Jingjing, Zhang Yanxia, Qu Meixia, Jiang Bin, Wang Wenyu, Automatic Classification of Spectra with IEF-SCNN, Universe，2023, 9(11), 477

Li Changhua, Zhang Yanxia, Cui Chenzhou , Fan Dongwei, Zhao Yongheng , Wu Xuebing, Zhang Jing-yi , Han Jun, Xu Yunfei, Tao Yihan, Li Shanshan, He Boliang, 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(20pp)

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

 

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, 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, 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 

Peng, Nanbo，Zhang Yanxia, Zhao Yongheng and Wu Xue-bing，Selecting Quasar Candidates by a SVM Classification System, 2012，MNRAS, 425, 2599

Wu Xue-Bing, Hao Guoqiang, Jia Zhendong, Zhang Yanxia and Peng Nanbo SDSS quasars in the WISE preliminary data release and quasar candidate selection with the optical/infrared colors, 2012，AJ, 144, 49

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 

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已指导学生

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  

现指导学生

李长华  博士研究生  0704Z1-天文技术与方法