Han Zhang, BS, MA

Research Interests: 

Previous work was about semi-supervised machine learning, noninvasive prenatal test and copy number variations. My current research interests are statistical learning, computational cancer genomics, immunotherapy and precision medicine. Specifically, I’m interested in developing computational and statistical tools for sequencing-based genomics study.

Doctoral Student, Department of Biomedical Informatics
Academic Advisor: 

Statement of career objectives:  Tenure-track professor and start and startup in digital healthcare



Zhang, H., Zhao, Y.-Y., Song, J., Zhu, Q.-Y., Yang, H., Zheng, M.-L., Xuan, Z.-L., Wei, Y., Chen, Y. & Yuan, P.-B. et al., Statistical approach to decreasing the error rate of noninvasive prenatal aneuploid detection caused by maternal copy number variation. Scientific reports 5, 16106 (2015).

Qi, H., Xuan, Z.-L., Du, Y., Cai, L.-R., Zhang, H., Wen, X.-H., Kong, X.-D., Yang, K., Mi, Y. & Fu, X.-X. et al., High resolution global chromosomal aberrations from spontaneous miscarriages revealed by low coverage whole genome sequencing. European Journal of Obstetrics & Gynecology and Reproductive Biology 224, 21-28 (2018).

Yin, X., Du, Y., Zhang, H., Wang, Z., Wang, J., Fu, X., Cui, Y., Chen, C., Liang, J. & Xuan, Z. et al., Identification of a de novo fetal variant in osteogenesis imperfecta by targeted sequencing-based noninvasive prenatal testing. Journal of Human Genetics 63, 1129-1137 (2018).

Hutson, N., Zhan, F., Graham, J., Murakami, M., Zhang, H., Ganaparti, S., Hu, Q., Yan, L., Ma, C., Liu, S., Xie, J., Wei, L. An adaptive method of defining negative mutation status for multi-sample comparison using next-generation sequencing. (In revision)


Google Scholar:  https://scholar.google.com/citations?user=xzacPQUAAAAJ&hl=en