Big data, Google and disease detection: the statistical story
主 题: Big data, Google and disease detection: the statistical story
报告人: Professor Samuel Kou (Harvard University)
时 间: 2017-12-21 14:00-15:00
地 点: Room 1114, Sciences Building No. 1
Abstract: Big data collected from the internet have generated significant interest in not only the academic community but also industry and government agencies. They bring great potential in tracking and predicting massive social activities. We focus on tracking disease epidemics in this talk. We will discuss the applications, in particular, Google Flu Trends, some of the fallacy and the statistical implications. We will propose a new model that utilizes publicly available online data to estimate disease epidemics. Our model outperforms all previous real-time tracking models for influenza epidemics at the national level of the US. An extended version of the model gives accurate tracking of Dengue fever in Asian and South American countries. We will also draw some lessons for big data applications.
About the speaker: Samuel Kou is Professor of Statistics at Harvard University. He received a bachelor's degree in computational mathematics from Peking University in 1997, followed by a Ph.D. in statistics from Stanford University in 2001. After completing his Ph.D., he joined Harvard University as an Assistant Professor of Statistics. He was promoted to a full professor in 2008. He is currently a Distinguished Visiting Professor at the National University of Singapore.
His research interests include stochastic inference in biophysics, chemistry and biology; protein folding; big data analytics; digital disease tracking; Bayesian inference for stochastic models; nonparametric statistical methods; model selection and empirical Bayes methods; and Monte Carlo methods.
He is the recipient of the COPSS (Committee of Presidents of Statistical Societies) Presidents' Award; the Guggenheim Fellowship; a US National Science Foundation CAREER Award; the Institute of Mathematical Statistics Richard Tweedie Award; the Raymond J. Carroll Young Investigator Award; and the American Statistical Association Outstanding Statistical Application Award. He is an elected Fellow of the American Statistical Association, an elected member of the International Statistical Institute, and an elected Fellow and a Medallion Lecturer of the Institute of Mathematical Statistics.