主 题: The Relative Size of Big Data: Perspectives from an Interdisciplinary Statistician
报告人: Prof. Bin Yu (Departments of Statistics and EECS, University of California at Berkeley)
时 间: 2013-12-26 14:00-15:00
地 点: 理科1号楼 1114（统计中心活动）
Big data problems occur when available computing resources (CPU, communication bandwidth, and memory) can not accommodate the computing demand on the data at hand. In this introductory overview talk, we provide perspectives on big data motivated by a collaborative project on coded aperture imaging with the advanced light source (ALS) group at the Lawrence Berkeley National Lab. In particular, we emphasize the key role in big data computing played by memory and communication bandwidth. Moreover, we briefly review available resource to monitor memory and time efficiency of algorithms in R and discuss active big data research topics. We conclude that the bottle-neck between statisticians and big data is human resource that includes interpersonal, leadership, and programming skills.
About the speaker（报告人介绍）：Bin Yu is Chancellor’s Professor in the Departments of Statistics and of Electrical Engineering & Computer Science at the University of California at Berkeley. She held faculty positions at the Univ of Wisconsin-Madison and Yale University and was a Member of Technical Staff at Bell Labs, Lucent. She was Chair of Department of Statistics from 2009 to 2012, and is a founding co-director of the Microsoft Lab on Statistics and Information Technology at Peking University, China.
She has published over 80 scientific papers in premier journals in statistics, machine learning, information theory, signal processing, remote sensing, neuroscience, and networks. She has served on many editorial boards for journals such as the Annals of Statistics, Journal of American Statistical Association, Journal of Machine Learning Research, and Technometrics.
She is a Fellow of the American Academy of Arts and Sciences. She was a Guggenheim Fellow in 2006, an Invited Speaker of ICIAM in 2011, and the Tukey Memorial Lecturer of the Bernoulli Society in 2012. She is a Fellow of AAAS, IEEE, IMS, and ASA.
She is President of IMS (Institute of Mathematical Statistics) and serving on the Scientific Advisory Board of IPAM at UCLA and on the Governing Board of ICERM at Brown University. She was co-chair of the National Scientific Committee of SAMSI, and served on the Board of Mathematical Sciences and Applications (BMSA) of the U.S. National Academy of Sciences.
