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He has been awarded the David Byar Young Investigator Award and has his papers published in Biometrika and the Journal of the Royal Statistical Society.
The theme of his research is to develop statistical methods and theory to quantify the uncertainty (confidence interval and hypothesis test) in modern data sets, which are characterized by high dimensionality, complexity and heterogeneity. He enjoys working at the interface of mathematical statistics, machine learning and stochastic optimization. He is also interested in applied projects in genomics, Neuroscience, epidemiology and clinical trials.
The theme of his research is to develop statistical methods and theory to quantify the uncertainty (confidence interval and hypothesis test) in modern data sets, which are characterized by high dimensionality, complexity and heterogeneity. He enjoys working at the interface of mathematical statistics, machine learning and stochastic optimization. He is also interested in applied projects in genomics, Neuroscience, epidemiology and clinical trials.
研究兴趣
论文共 31 篇作者统计合作学者相似作者
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Yang Ning, Jingyi Duan
Chapman and Hall/CRC eBookspp.283-292, (2023)
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arxiv(2022)
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ANNALS OF STATISTICSno. 2 (2022): 640-672
ANNALS OF STATISTICSno. 4 (2022): 2284-2305
arXiv (Cornell University) (2022)
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