Seyoung Kim Postdoctoral Fellow School of Computer Science Carnegie Mellon University Email : s ykim (you need to replace the 's' with 'sss') at cs.cmu.edu Office : GHC 8229

I am currently a project scientist with Prof. Eric Xing in Machine Learning Department at Carnegie Mellon University. I received Ph.D. in Computer Science from the University of California, Irvine, under the supervision of Prof. Padhraic Smyth, and B.S. in computer engineering from Seoul National University, Korea. My research interests are in statistical machine learning with an application to problems in computational biology.

Publications

• Tree-Guided Group Lasso for Multi-Task Regression with Structured Sparsity
  S. Kim, E. P. Xing. Manuscript, arXiv:0909.1373, communicated September 2009. [pdf]

• Heterogeneous Multitask Learning with Joint Sparsity Constraints
  X. Yang, S. Kim and E. P. Xing. Advances in Neural Information Processing Systems (NIPS), 2009, to appear

• Statistical estimation of correlated genome associations to a quantitative trait network
  S. Kim, E. P. Xing. PLoS Genetics 5(8): e1000587, 2009. [link] [software]

• A multivariate regression approach to association analysis of a quantitative trait network
  S. Kim, K. Sohn, E. P. Xing. Proceedings of the 17th Conference on Intelligent Systems for Molecular Biology (ISMB), 2009. [pdf]

• Feature selection via block-regularized regression
  S. Kim, E. P. Xing. Proceedings of the 24th Conference on Uncertainty in AI (UAI), 2008. [pdf]

• Hierarchical Dirichlet processes with random effects
  S. Kim, P. Smyth. Advances in Neural Information Processing Systems (NIPS), 2006. [pdf]

• A nonparametric Bayesian approach to detecting spatial activation patterns in fMRI data
  S. Kim, P. Smyth, H. Stern. Proceedings of the 9th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2006. [pdf]

• Segmental hidden Markov models with random effects for waveform modeling
  S. Kim, P. Smyth. Journal of Machine Learning Research, 7(Jun):945-969, 2006. [pdf]

• Parametric response surface models for analysis of multi-site fMRI data
  S. Kim, P. Smyth, H. Stern, J. Turner. Proceedings of the 8th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2005. [pdf]

• Variance component analysis of a multi-site fMRI study
  S. Kim, H. Stern, P. Smyth. Technical Report UCI-TR 04-14, 2004.

• Modeling waveform shapes with random effects segmental hidden Markov models
  S. Kim, P. Smyth, S. Luther. Proceedings of the 20th Conference on Uncertainty in AI (UAI), 2004. [pdf] (longer version as Technical Report UCI-ICS 04-05, March 2004. [pdf])

Teaching

• Instructor, ICS 171 Introduction to AI, Summer 2006, UC Irvine.
• Teaching Assistant
  • ICS 23 Fundamental Data Structures, Spring 2003, UC Irvine.
  • ICS 173 Neural Networks, Winter 2003, UC Irvine.
  • ICS 80 Java for C++ Programmers, Fall 2002, UC Irvine.