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Computer Science
UK
2023

D-Index & Metrics

Computer Science

D-Index
60
Citations
23793
World Ranking
3169
National Ranking
1535

Research.com Recognitions

  • 2023 - Research.com Computer Science in United Kingdom Leader Award
  • 2011 - IEEE Fellow For contributions to independent component analysis algorithms

Overview

Te-Won Lee is affiliated with Qualcomm in the United States, contributing to research and development within the technology industry. Their work is recognized for contributions to independent component analysis algorithms, which led to their recognition as an IEEE Fellow in 2011.

The IEEE Fellow award was granted specifically for contributions to independent component analysis algorithms.

Their professional activities include collaborative efforts within Qualcomm, although specific co-authors are not listed.

There are no publicly available records of their recent papers, book publications, or frequent publication venues, which limits detailed insight into the specific outlets for their research dissemination.

Specific fields and subfields of study related to Te-Won Lee's research are not detailed in available data, nor are distinct main topics of work beyond the noted area of independent component analysis.

This profile highlights the scientist's association with a major technology company and a notable professional distinction, while detailed publication records and research themes remain unspecified in available public information.

Best Publications

  • Removing electroencephalographic artifacts by blind source separation.

    Tzyy-Ping Jung;Tzyy-Ping Jung;Scott Makeig;Colin Humphries;Te-Won Lee;Te-Won Lee

  • Independent component analysis using an extended infomax algorithm for mixed subgaussian and supergaussian sources

    Te-Won Lee;Mark Girolami;Terrence J. Sejnowski;Terrence J. Sejnowski

  • Independent component analysis

    Te-Won Lee

  • Dictionary learning algorithms for sparse representation

    Kenneth Kreutz-Delgado;Joseph F. Murray;Bhaskar D. Rao;Kjersti Engan

  • Independent Component Analysis: Theory and Applications

    Te-Won Lee

  • Imaging brain dynamics using independent component analysis

    T.-P. Jung;S. Makeig;M.J. McKeown;A.J. Bell

  • Extended ICA Removes Artifacts from Electroencephalographic Recordings

    Tzyy-Ping Jung;Colin Humphries;Te-Won Lee;Scott Makeig

  • Blind source separation of more sources than mixtures using overcomplete representations

    Te-Won Lee;M.S. Lewicki;M. Girolami;T.J. Sejnowski

  • A Unifying Information-Theoretic Framework for Independent Component Analysis

    Te Won Lee;Te Won Lee;M. Girolami;A. J. Bell;T. J. Sejnowski;T. J. Sejnowski

  • Spatially independent activity patterns in functional MRI data during the Stroop color-naming task

    Martin J. McKeown;Tzyy-Ping Jung;Scott Makeig;Greg Brown

  • Blind Source Separation Exploiting Higher-Order Frequency Dependencies

    Taesu Kim;H.T. Attias;Soo-Young Lee;Te-Won Lee

  • Blind speech separation

    Shoji Makino;Hiroshi Sawada;Te-Won Lee

  • On the multivariate Laplace distribution

    T. Eltoft;Taesu Kim;Te-Won Lee

  • Independent vector analysis: an extension of ICA to multivariate components

    Taesu Kim;Torbjørn Eltoft;Te-Won Lee

  • ICA mixture models for unsupervised classification of non-Gaussian classes and automatic context switching in blind signal separation

    Te-Won Lee;M.S. Lewicki;T.J. Sejnowski

  • Comparison of machine learning and traditional classifiers in glaucoma diagnosis

    Kwokleung Chan;Te-Won Lee;P.A. Sample;M.H. Goldbaum

  • Blind Separation of Delayed and Convolved Sources

    Te-Won Lee;Anthony J. Bell;Russell H. Lambert

  • Mobile device location estimation using environmental information

    Taesu Kim;Kisun You;Te-Won Lee

  • Removing electroencephalographic artifacts: comparison between ICA and PCA

    T.-P. Jung;C. Humphries;T.-W. Lee;S. Makeig

  • Touchless sensing and gesture recognition using continuous wave ultrasound signals

    Ren Li;Te-Won Lee;Hui-Ya L. Nelson;Samir K. Gupta

  • INDEPENDENT COMPONENT ANALYSIS OF BIOMEDICAL SIGNALS

    Tzyy-Ping Jung;Scott Makeig;Te-Won Lee;Martin J. McKeown

Frequent Co-Authors

Terrence J. Sejnowski
Terrence J. Sejnowski Salk Institute for Biological Studies
Linda M. Zangwill
Linda M. Zangwill University of California, San Diego
Tzyy-Ping Jung
Tzyy-Ping Jung University of California, San Diego
Erik Visser
Erik Visser Qualcomm (United Kingdom)
Scott Makeig
Scott Makeig University of California, San Diego
Martin J. McKeown
Martin J. McKeown University of British Columbia
Seung-Schik Yoo
Seung-Schik Yoo Brigham and Women's Hospital
Vicente J. Iragui
Vicente J. Iragui University of California, San Diego
Mark Girolami
Mark Girolami University of Cambridge
Bhaskar D. Rao
Bhaskar D. Rao University of California, San Diego

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