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Youngjoo Kim

Postdoc guest researcher

  • Room number: 487 (Bernoulliborg)
  • E-mail: lyoungjookiml [at]

Youngjoo Kim received a Ph.D. in Computer Science from Bernoulli Institute for Mathematics, Computer Science and Artificial Intelligence, University of Groningen, The Netherlands, in 2023. She was supervised by Prof. Dr. Alexandru Telea, Prof. Dr. S. C. Trager and Prof. Dr. Jos Roerdink. She was enrolled in the Marie Skłodowska-Curie EU’s Horizon 2020 and Data Science and Systems Complexity (DSSC COFUND) Doctoral program.


Visual analytics and machine learning for the exploration and analysis of high-dimensional data with applications in biomedicine and astronomy.


 Introduction to Computing Science (2018, 2019, 2020)
 Image Processing (2019)
 Supervision for Honor's College Student (2019)
 Statistics for Astronomy (2020)


Please refer to Youngjoo's publication page.

M. Espadoto, Y. Kim, S. C. Trager, J. B. T. M. Roerdink, and A. C. Telea, “Stabilizing and Simplifying Sharpened Dimensionality Reduction using Deep Learning,” Springer, SN Computer Science, Mar., 2023.

Y. Kim, M. Espadoto, A. C. Telea, S. C. Trager, and J. B. T. M. Roerdink, “SDR-NNP: Sharpened Dimensionality Reduction with Neural Networks,” 13th International Conference on Information Visualization Theory and Applications (IVAPP/VISIGRAPP) held from Feb., 2022.

Y. Kim, A. C. Telea, S. C. Trager, and J. B. T. M. Roerdink, “Visual Cluster Separation Using High-Dimensional Sharpened Dimensionality Reduction,” Information Visualization, vol. 21, no. 3, pp. 197-219, 2022.

J. Ryu, Y. Kim, S. M. Lee, D. Sim, K. S. Park and C. Park, “Multivariate Time-Frequency Analysis of Uterine Electromyogram for Separation of Term and Preterm Labor,” Journal of Electrical Engineering & Technology, Vol. 14, No. 2, pp. 897-916. 2019.

Y. Kim, J. You, H. Lee, S.M. Lee, and C. Park, “Correlation Assisted Strong Uncorrelating Transform Complex Common Spatial Patterns for Spatially Distant Channel Data,” Computational Intelligence and Neuroscience, May 15, 2018.

G.-S. Ryu, J. You, V. Kostianovskii, E.-B. Lee, Y. Kim, C. Park, and Y.-Y. Noh, “Flexible and Printed PPG Sensors for Estimation of Drowsiness.” IEEE Transactions on Electron Devices, Vol. 65, No. 7, pp. 2997-3004, 2018.

Y. Kim, J. Ryu, K.K. Kim, C.C Took, D.P. Mandic, C. Park, “Motor Imagery Classification Using Mu and Beta Rhythms of EEG with Strong Uncorrelating Transform Based Complex Common Spatial Patterns,” Computational Intelligence and Neuroscience, Oct 3, 2016.

K.B. Lee, K.K. Kim, J. Song, J. Ryu, Y. Kim, C. Park, “Estimation of Brain Connectivity during Motor Imagery Tasks using Noise-Assisted Multivariate Empirical Mode Decomposition,” JEET, vol. 11, 2016.