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You are here: Home / Additional Features / A Statistician's Life / Bin Yu

Bin Yu

March 1, 2018 Leave a Comment

Affiliation
Chancellor’s Professor, Departments of Statistics and Electrical Engineering and Computer Sciences, University of California at Berkeley

Educational Background
Peking University: BS, Mathematics (1984)
University of California at Berkeley: MA and PhD, Statistics (1987, 1990)

About Bin
Bin Yu was born in Harbin, China, and grew up during the Cultural Revolution. Her own and her family members’ experiences during the revolution shaped her values of fairness, integrity, kindness, and hard work. Her interest in mathematics was initiated when she was in the third grade and her cousin, Dawei Huang, gave her a math book. She benefited greatly from the excellent mentorship of her middle-school teacher, Jianye Chen, for training her competence in mathematics and his advice during her college days.

Bin’s current research interests focus on statistics and machine learning algorithms and theory for solving high-dimensional data problems. Her lab is engaged in interdisciplinary research with scientists from genomics, neuroscience, precision medicine, and political science.

She is a member of the US National Academy of Sciences and was a Guggenheim Fellow in 2006. She was president of the Institute of Mathematical Statistics (IMS) in 2013–2014 and the Rietz Lecturer of IMS in 2016. She has been invited to speak on many occasions, including at the International Congress on Industrial and Applied Mathematics in 2011 and the Tukey Memorial of the Bernoulli Society in 2012. She is a Fellow of the ASA, IMS, American Academy of Arts and Sciences, and Institute of Electrical and Electronics Engineers.

Bin is not only a member of many societies, but has also served or is serving on many editorial boards, including the Journal of Machine Learning Research, Annual Reviews in Statistics, Annals of Statistics, and Journal of the American Statistical Association.

Filed Under: A Statistician's Life, Celebrating Women in Statistics Tagged With: Cultural Revolution, Guggenheim Fellow, IMS, Journal of Machine Learning, Research, Rietz Lecturer, US National Academy of Sciences

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