Namgil Lee


Research Scientist

Cichocki Laboratory for Advanced Brain Signal ProcessingRIKEN Brain Science Institute

Address: RIKEN BSI, 2-1 Hirosawa, Wako, Saitama, 351-0198, Japan

E-mail: namgil(at)kaist.ac.kr, namgil.lee(at)riken.jp

Tel: +81-48-462-1111 ex.7173
Fax: +81-48-462-1554



About Me

I am a research scientist at RIKEN Brain Science Institute in Japan. I am currently working on advanced signal processing methods using tensor decomposition and tensor networks, for applications in neuroscience. My research background lies in mathematics, statistics, and machine learning. I received my Ph.D. in statistics from the department of mathematical sciences at KAIST, South Korea. During my Ph.D., I worked on interesting research topics like graphical modeling and multivariate time series modeling under the supervision of Prof. Sung-Ho Kim. Before joining Prof. Kim's Lab, I received my M.S. degree in machine learning under the supervision of  Prof. Rhee Man Kil, focusing on computational learning theory and nonlinear regression modeling. 

Research Interests:

  • High-dimensional Statistical Modeling
  • Tensor Decomposition for Big Data Signal Processing
  • Machine Learning --- Kernel Methods, Graphical Models, Artificial Neural Network, Learning Theory
  • FMRI/EEG for Analysis of Functional Brain Connectivity


News

  • Shift to a new position Recently I joined the Department of Statistics, Kangwon National University, Chuncheon, South Korea. My previous email addresses are still valid. I hope to update this website soon.
    2017. 3. 22. 오전 12:38에 Namgil Lee님이 게시
  • "Excellent Paper Award" at the ICONIP 2016 Our paper "Nonnegative Tensor Train Decompositions for Multi-Domain Feature Extraction and Clustering" received the "Excellent Paper Award"at the ICONIP 2016, 16-21 October 2016, Kyoto, Japan. This is ...
    2016. 10. 24. 오전 6:08에 Namgil Lee님이 게시
  • ICONIP2016, Kyoto, Japan, 16-21 Oct 2016 I will participate in the conference: The 23rd International Conference on Neural Information Processing (ICONIP2016). Our title of the presentation is "Nonnegative Tensor Train Decompositions for Multi-Domain Feature Extraction ...
    2016. 9. 5. 오후 11:24에 Namgil Lee님이 게시
7개의 게시물 중 1 - 3 더보기 »

Code

  • Singular Value Decomposition Using Tensor Train (N.Lee & A.Cichocki, 2015) ALS and MALS algorithms for EVD/SVD in MATLAB - v201502REFERENCE:Namgil Lee, Andrzej Cichocki. Estimating a Few Extreme Singular Values and Vectors for Large-Scale Matrices in Tensor Train ...
    2015. 8. 25. 오전 7:23에 Namgil Lee님이 게시
  • Conversion of Categorical Variables (N. Lee & J.-M. Kim, 2010) Matlab software for conversion of mixed categorical and numerical variables into numerical variables for binary classificationREFERENCE:Namgil Lee and Jong-Min Kim, Conversion of categorical variables into numerical variables ...
    2016. 3. 17. 오후 7:50에 Namgil Lee님이 게시
2개의 게시물 중 1 - 2 더보기 »