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Faculty

프린트페이스북

Heeyoung Kim

Ph.D. Industrial Engineering,
Georgia Institute of Technology, 2011

Education

  • 2003, KAIST, Industrial Engineering, B.S.
  • 2005, KAIST, Industrial Engineering, M.S
  • 2008, Georgia Institute of Technology, Statistics, M.S.
  • 2011, Georgia Institute of Technology, Industrial Engineering, Ph.D.

Research experience

  • 2011, Georgia Institute of Technology, Industrial Engineering, Ph.D.
  • 2013.12-present : Assistant Professor, Department of Industrial & Systems Engineering, KAIST

Research area

Data Mining  
1
In the areas of statistical data mining, research interests include classification, clustering, and dimension reduction, especially for functional data and high-dimensional data.
Sample paper: “A single interval based classifier” [Link]

Nonparametric Regression 
2
We study an adaptive nonparametric regression method for estimating functions with spatially varying roughness. In particular, in the framework of smoothing splines, an asymptotically optimal choice of the locally adaptive penalty is studied.
Sample paper: “Locally optimal adaptive smoothing splines” [Link]

Spatial Data Modeling 
3
We study statistical methods for spatial data problems. Research interests include spatial anomaly detection and hierarchical modeling for spatial data.
Sample paper: “Spatiotemporal event detection in mobility networks” [Link]

Design of Experiments 
4
We study effective methods for a sequential design of experiments under the situation that resources are limited, response surface is complex, and tight tolerance is required.
Sample paper: “Layers of experiments with adaptive combined design”

Selected publications

  • Heeyoung Kim and Xiaoming Huo (2014), “Asymptotic optimality of a multivariate version of the generalized cross validation in adaptive smoothing splines”, Electronic Journal of Statistics, 8, 159-183.
  • Heeyoung Kim, Xiaoming Huo, Meghan Shilling, and Hy Tran (2014), “A Lipschitz regularity-based statistical model, with applications in coordinate metrology,” IEEE Transactions on Automation Science and Engineering, 11(2), 327-337
  • Heeyoung Kim, Xiaoming Huo, and Jianjun Shi (2014), “A single interval based classifier,”Annals of Operations Research, 216, 307–325. Heeyoung Kim and Xiaoming Huo (2013), “Optimal sampling and curve interpolation via wavelets,” Applied Mathematics Letters, 26(7), 774-779.
  • Heeyoung Kim and Xiaoming Huo (2012), “Locally optimal adaptive smoothing splines,” Journal of Nonparametric Statistics, 24(3), 665-680.
  • Kichun Lee, Alexander Gray, and Heeyoung Kim (2012), “Dependence maps, a dimensionality reduction with dependence distance for high-dimensional data,” Data Mining and Knowledge Discovery, 26(3), 512-532.
  • Tom Au, Rong Duan, Heeyoung Kim, and Guang-Qin Ma (2010),“Spatiotemporal event detection in mobility networks,” Proceedings of the 10th IEEE International Conference on Data Mining, 28-37.

Teaching

  • ISYE2028 Basic Statistical Methods, Georgia Institute of Technology
  • IE241 Engineering Statistics I, KAIST
  • IE341 Engineering Statistics II, KAIST

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