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Dr. YANG Yi (楊屹博士)

BS (Chu Kochen Honors College, Zhejiang University), MS and PhD (University of Minnesota)

Assistant Professor

Contact Information

Office: G5753 YEUNG
Phone: 34424181
Fax: 34420613
Email: yi.yang@cityu.edu.hk
Web: Personal Homepage

Research Interests

  • Statistical Genetics
  • Knockoff Statistics
  • Bayesian Statistics
  • High-Dimensional Variable Selection
Dr. Yang received a PhD in Biostatistics from the University of Minnesota and a BS in Management Information Systems from Chu Kochen Honors College, Zhejiang University. Prior to joining CityU, he served as a postdoctoral research scientist in the Department of Biostatistics at Columbia University under the supervision of Professor Iuliana Ionita-Laza. He is also a four-time recepient of the First Prize in the National Olympiad in Informatics (NOI), China.

Dr. Yang's research focuses on variable selection methods for high-dimensional data using knockoff statistics, statistical machine learning, and Bayesian hierarchical models. He has developed a number of statistical methods to identify risk variants for human diseases in genetic data with complex hierarchical and correlation structures. His research is supported by the Research Grants Council of Hong Kong (RGC) Early Career Scheme 21303323 (sole PI).


Research Grants

  • Statistical methods for variable selection with false discovery rate control and applications to human genetic data, Early Career Scheme (傑出青年學者計劃), Research Grants Council of Hong Kong, 2024 - 2026, Yi Yang (PI).
  • Prediction of patient mortality in intensive care units using machine learning with controlled variable selection, Strategic Interdisciplinary Research Grant, City University of Hong Kong, 2023 - 2025, Linyan Li (PI), Yi Yang (Co-PI).


Publications Show All Publications Show Prominent Publications


Journal

  • Yang, Yi. , Wang, Qi. , Wang, Chen. , Buxbaum, Joseph. & Ionita-Laza, Iuliana. (May 2024). KnockoffHybrid: A knockoff framework for hybrid analysis of trio and population designs in genome-wide association studies. The American Journal of Human Genetics. 111(7). 1448 - 1461. doi:10.1016/j.ajhg.2024.05.003
  • Yang, Yi. , Wang, Chen. , Liu, Linxi. , Buxbaum, Joseph. , He, Zihuai. & Ionita-Laza, Iuliana. (Oct 2022). KnockoffTrio: A knockoff framework for the identification of putative causal variants in genome-wide association studies with trio design. The American Journal of Human Genetics. 109(10). 1761 - 1776. doi:10.1016/j.ajhg.2022.08.013
  • Yang, Yi. , Basu, Saonli. & Zhang, Lin. (Feb 2022). A Bayesian hierarchically structured prior for gene-based association test with multiple traits in genome-wide association studies. Genetic epidemiology. 46(1). 63 - 72. doi:10.1002/gepi.22437
  • Yang, Yi. , Basu, Saonli. & Zhang, Lin. (Jun 2021). A Bayesian hierarchically structured prior for rare‐variant association testing. Genetic epidemiology. 45(4). 413 - 424. doi:10.1002/gepi.22379
  • Yang, Yi. , Basu, Saonli. & Zhang, Lin. (Mar 2020). A Bayesian hierarchical variable selection prior for pathway-based GWAS using summary statistics. Statistics in medicine. 39(6). 724 - 739. doi:10.1002/sim.8442
  • Yang, Yi. , Basu, Saonli. , Mirabello, Lisa. , Spector, Logan. & Zhang, Lin. (May 2018). A Bayesian gene-based genome-wide association study analysis of osteosarcoma trio data using a hierarchically structured prior. Cancer Informatics. 17. doi:10.1177/1176935118775103


Openings

  • I am looking for highly motivated Ph.D. students with a background in statistics, mathematics, computer science, data science, bioinformatics, or related fields. Please send your CV and transcript(s) to yi.yang@cityu.edu.hk if you are interested. Please see https://yiyangphd.github.io/openings/ for more details.


Last update date : 31 Jul 2024