News

Articles 92

Date: 2013.5.8(Wed.) 16:00

Venue: Wooribyul Seminar room. Dept. of EE(E3-2)

Speaker: Professor Yeonseung Chung/Department of Mathematical Sciences/KAIST

Title:  Introduction to Nonparameteric Bayesian Statistical Modeling


Abstract : 

In this talk, a brief introduction to Nonparameteric (NP) Bayesian statistical modeling will be given. Following the description of some key components of Bayesian statistical modeling, the lecture starts with some complicated statistical modeling problems for which parametric modeling may have limitations and moves to NP Bayes methodology for the complex modeling. Focuses will be on NP Bayes approaches involving Gaussian process (GP), Dirichlet process (DP), extensions of DP, Beta process, and Indian Buffet process. If time permits, computation-based inference procedure focusing on Markov Chain Monte Carlo (MCMC) will also be discussed. The lecture will be concluded with a summary and some discussions of future research directions.

 

Bio:

ACADEMIC TRAINING

B.S. in Statistics, Korea University, Korea, 2000

M.S. in Biostatistics, University of North Carolina, Chapel Hill, USA, 2005

Ph.D. in Biostatistics, University of North Carolina, Chapel Hill, USA, 2009

Dissertation : Nonparamertric Bayes inference for conditional distribution modeling

Advisor : Prof. David Dunson

 

ACADEMIC APPOINTMENTS

Assistant Professor, Dept. of Mathematical Sciences, KAIST, Korea, January, 2011 - present

Research Associate, Dept. of Biostatistics, Harvard School of Public Health, USA, 2010 - 2011

Post-doctoral Research Fellow, Dept. of Biostatistics, Harvard School of Public Health, USA, 2009 - 2010

Pre-doctoral Research Fellow, Division of Biostatistics, NIEHS, NIH, USA, 2007-2009

Graduate Industry Trainee, GlaxoSmithKline, Durham, USA, 2005-2007

Graduate Research Assistant, Lineberger Comprehensive Cancer Center, UNC-CH, USA. 2003-2005

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