Research Areas

  • Data mining and machine learning
  • Nonparametric and semiparametric statistical methods
  • Functional data analysis
  • Spatio-temporal data analysis
  • Design of experiments
  • Applications in manufacturing, telecommunications, and healthcare


International Journal Papers 

  1. K. Kim, H. Zabihi, H. Kim, and U. Lee (2017), “TrailSense: a crowdsensing system for detecting risky mountain trail segments with walking pattern analysis,” Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT), accepted.
  2. H. Kim and J. Lee (2017), “Hierarchical spatially varying coefficient process model ,” Technometrics, accepted.
  3. Y. Jung and H. Kim (2017), “Detection of PVC by Using a Wavelet-based Statistical ECG Monitoring Procedure,” Biomedical Signal Processing and Control, 36, 176-182.
  4. H. Kim, J. T. Vastola, S. Kim, J.-C. Lu, and M. A. Grover (2017), “Incorporation of engineering knowledge into the modeling process: a local approach,”  International Journal of Production Research, 55(20), 5865-5880.
  5. S. Kim, H. Kim, and Y. Park (2017), “Early detection of vessel delays using combined historical and real-time information,” Journal of the Operational Research Society, 68(2), 182-191.
  6. H. Kim, J. T. Vastola, S. Kim, J.-C. Lu, and M. A. Grover (2017), “Batch sequential minimum energy design with design region adaptation,” Journal of Quality Technology, 49(1), 11-26.
  7. H. Kim, S. Kim, J. Deng, J.-C. Lu, K. Wang, C. Zhang, M. A. Grover, and B. Wang (2017),  “An integrated holistic model of a complex process,” International Journal of Advanced Manufacturing Technology, 89(1), 1137-1147.
  8. W. Soh, H. Kim, and B.-J. Yum (2016), “A multivariate loss function approach to robust design of systems with multiple performance characteristics”, Quality and Reliability Engineering International, 32(8), 2685-2700.
  9. S. Kim, H. Kim, and Y. Namkoong (2016), “Ordinal classification of imbalanced data with application in emergency and disaster information services”, IEEE Intelligent Systems, 31(5), 50-56.
  10. S. Kim and H. Kim (2016), “A new metric of absolute percentage error for intermittent demand forecasts,” International Journal of Forecasting, 32(3), 669–679.
  11. W. Soh, H. Kim, and B.-J. Yum (2015), “Application of kernel principal component analysis to multi-characteristic parameter design problems,” Annals of Operations Research, accepted.
  12. S. Kim, H. Kim, R.W. Lu, J.-C. Lu, M.J. Casciato, and M. A. Grover (2015), “Adaptive combined space-filling and D-optimal designs,” International Journal of Production Research, 53(17), 5354–5368.
  13. S. Kim, H. Kim, J.-C. Lu, M.J. Casciato, M.A. Grover, D.W. Hess, R.W. Lu, and X. Wang (2015), “Layers of experiments with adaptive combined design,” Naval Research Logistics, 62(2), 127-142.
  14. H. Kim and X. Huo (2014), “Asymptotic optimality of a multivariate version of the generalized cross validation in adaptive smoothing splines,” Electronic Journal of Statistics, 8, 159-183.
  15. H. Kim, X. Huo, M. Shilling, and H. Tran (2014), “A Lipschitz regularity-based statistical model, with applications in coordinate metrology,” IEEE Transactions on Automation Science and Engineering, 11(2), 327-337.
  16. H. Kim, X. Huo, and J. Shi (2014), “A single interval based classifier,”Annals of Operations Research, 216, 307-325.
  17. H. Kim and X. Huo (2013), “Optimal sampling and curve interpolation via wavelets,” Applied Mathematics Letters, 26(7), 774-779.
  18. K. Lee, A. Gray, and H. Kim (2013), “Dependence maps, a dimensionality reduction with dependence distance for high-dimensional data,” Data Mining and Knowledge Discovery, 26(3), 512-532.
  19. H. Kim and X. Huo (2012), “Locally optimal adaptive smoothing splines,” Journal of Nonparametric Statistics, 24(3), 665-680.

Selected International Conference Papers

  1. M. Choy, D. Kim, J.-G. Lee, H. Kim, and H. Motoda (2016), “Looking back on the current day: interruptibility prediction using daily behavioral features,” ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp), 1004-1015. (Acceptance rate: 24 %)
  2. W. Lee, Y. Lee, H. Kim, and I.-C. Moon (2016), “Bayesian nonparametric collaborative topic Poisson factorization for electronic health records-based phenotyping,” International Joint Conference on Artificial Intelligence (IJCAI), 2544-2552. (Acceptance rate: 25 %)
  3. T. Au, R. Duan, H. Kim, and G.-Q. Ma (2010),“Spatiotemporal event detection in mobility networks,” IEEE International Conference on Data Mining (ICDM), 28-37. (Acceptance rate: 19 %)

Domestic Journal Papers

  1. Y. Jung and H. Kim (2016), “Detection of atrial fibrillation using Markov regime switching models of heart rate intervals,” Journal of the Korean Institute of Industrial Engineers, 42(4), 290-295.  (First place in the Master’s student research paper contest, Fall Conference of Korean Institute of Industrial Engineers, 2015)