Tian Zheng

Tian Zheng is associate professor of Statistics at Columbia University. She obtained her PhD from Columbia in 2002. Her research is to develop novel methods and improve existing methods for exploring and analyzing interesting patterns in complex data from different application domains. Her current projects are in the fields of statistical genetics, bioinformatics and computational biology, feature selection and classification for high dimensional data, and network analysis. Especially, Dr. Zheng have been developing statistical and computational tools for high dimensional data, searching for genetic interactions associated with complex human disorders, quantifying social structure and studying hard-to-reach populations using survey questions, with more than 40 peer-reviewed publications in journals including JASA, AOAS and PNAS. Her work was recognized with the 2008 Outstanding Statistical Application Award from the American Statistical Association, The Mitchell Prize from ISBA and a Google research award. She is on the editorial board of Statistical Analysis and Data Mining and Frontier in Genetics. She was Associate Editor for JASA from 2007 to 2013.

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Statistical Thinking for Data Science and Analytics (edX) EdX
Columbia University,ColumbiaX

Statistical Thinking for Data Science and Analytics (edX)

Dive into Statistical Thinking for Data Science and Analytics on edX and gain a robust understanding of statistics as the cornerstone of data science. This course will guide you through essential concepts like designing data collections, deriving insights from visualizations, making data-based decisions, and constructing predictive models. Ideal for those new to data science or looking to deepen their analytical skills.

Self Paced
Self-Paced
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