Seung Jun Shin
I am Seung Jun Shin (신승준), an associate professor in the Department of Statistics, Korea university. My research is broadly related to statistical machine learning, data science, and their applications. In particular, I am interested in recovering informative signals buried in large-scale data, and currently serving as an editorial reviewer of Journal of Machine Learning Research. Application areas that I have been involved include, but not limited to, genetics, medicine, environmental science, political science, and marketing. My current research topics are:
Supervised Dimension Reduction: Sufficient Dimension Reduction, Variable Selection via Regularization, Independent Feature Screening for Ultrahigh Dimensional Data
Kernel Machines: Support Vector Machine, Kernel Quantile Regression, Piecewise Linear Regularization Paths, ROC-optimizing Classifier.
Statistical Computing: non/convex optimization, Bootstrap, Markov Chain Monte Carlo (MCMC) Sampling.
Bayesian Modeling: Nonparametric Function Estimation via Bernstein Polynomials, Bayesian Survival Data Analysis
Before joining at Korea University, I worked as a postdoc fellow in the University of Texas MD Anderson cancer center at Houston Texas (Mentors: Dr. Wenyi Wang and Dr. Ying Yuan) . I obtained my PhD degree in statistics at North Carolina state university in 2013 under supervision of Dr. Yichao Wu and Dr. Hao Helen Zhang, and Bachelor and Master degrees at Korea university. I am a recipient of IMS Travel Award (previously known as Laha Award) in JSM 2012.