Dr. Jaegul Choo

Research Scientist, School of Computational Science and Engineering, Georgia Tech




Curriculum Vitae
Research Statement
Teaching Statement

Postal Address: 266 Ferst Drive
Atlanta, Georgia 30332

Office: Room 1305 Klaus Advanced Computing Building

Phone:

678.665.2332  Cell

E-Mail: jaegul.choo[at]cc[dot]gatech[dot]edu

About me

I am a Research Scientist at Georgia Tech. I received Ph.D in School of Computational Science and Engineering in 2013. I earned my M.S. in Electrical and Computer Engineering. My advisor is Dr. Haesun Park. During the summer in 2009 and 2010, I worked at National Visualization and Analytics Center (NVAC) in Pacific Northwest National Laboratory. I earned my B.S. in Electrical and Computer Engineering at Seoul National University.

 

Research Interest

I'm broadly interested in integrating data mining techniques in visual analytics. Among various techniques, I'm primarily interested in dimension reduction and clustering, which play essential roles in visualizing and interacting with large-scale high-dimensional data. My research focuses on making them visually and semantically meaningful and real-time interactive.

I am currently on the job market. Please check out my CV, research statement, and teaching statement and contact me if you are interested.

 

Publications

2014

  • Weakly Supervised Nonnegative Matrix Factorization for User-Driven Clustering
    Jaegul Choo, Changhyun Lee, Chandan K. Reddy, and Haesun Park
    Data Mining and Knowledge Discovery (DMKD), 2014, Accepted.
  • VisIRR: Visual Analytics for Information Retrieval and Recommendation for Large-scale Document Data
    Jaegul Choo, Changhyun Lee, Hannah Kim, Hanseung Lee, Zhicheng Liu, Ramakrishnan Kannan, Charles D. Stolper, John Stasko, Barry L. Drake, and Haesun Park
    IEEE Conference on Visual Analytics Science and Technology (VAST-Poster), 2014, Accepted.
  • PIVE: A Per-Iteration Visualization Environment for Supporting Real-time Interactions with Computational Methods
    Jaegul Choo, Jaegul Choo, Changhyun Lee, Hannah Kim, Hanseung Lee, Barry L. Drake, and Haesun Park
    IEEE Conference on Visual Analytics Science and Technology (VAST-Poster), 2014, Accepted.
  • Nonnegative Matrix Factorization for Interactive Topic Modeling and Document Clustering
    Da Kuang, Jaegul Choo, Jaegul Choo, and Haesun Park
    Partitional Clustering Algorithms (Book Chapter), Springer, 2014, Accepted.
  • To Gather Together for a Better World: Understanding and Leveraging Communities in Micro-lending Recommendation
    Jaegul Choo, Daniel Lee, Bistra Dilkina, Hongyuan Zha, and Haesun Park
    International Conference on World Wide Web (WWW), pages 249-260, 2014.
    [PDF][SLIDE]
  • Understanding and Promoting Micro-finance Activities in Kiva.org
    Jaegul Choo, Changhyun Lee, Daniel Lee, Hongyuan Zha, and Haesun Park
    ACM International Conference on Web Search and Data Mining (WSDM), pages 583-592, 2014.
    [PDF][SLIDE]
  • Visual Analytics for Interactive Exploration of Large-scale Document Data via Nonnegative Matrix Factorization
    Jaegul Choo, Barry L. Drake, and Haesun Park
    BigData Innovators Gathering (Demo Paper) (BIG), 2014.
    [PDF][SLIDE]

2013

  • UTOPIAN: User-driven Topic Modeling Based on Interactive Nonnegative Matrix Factorization
    Jaegul Choo, Changhyun Lee, Chandan K. Reddy, and Haesun Park
    IEEE Transactions on Visualization and Computer Graphics (TVCG), Volume 19, Number 12, pages 1992-2001, 2013
    [PDF][SLIDE][VIDEO]
  • Customizing Computational Methods for Visual Analytics with Big Data
    Jaegul Choo and Haesun Park
    IEEE Computer Graphics and Applications (CG&A), Volume 33, Issue 4, pages 22-28, 2013
    [PDF]
  • Combining Computational Analyses and Interactive Visualization for Document Exploration and Sensemaking in Jigsaw
    Carsten Görg, Zhicheng Liu, Jaeyeon Kihm, Jaegul Choo, Haesun Park and John Stasko
    IEEE Transactions on Visualization and Computer Graphics (TVCG), Volume 19, Number 10, pages 1646-1663, 2013
    [PDF][VIDEO]
  • An interactive visual testbed system for dimension reduction and clustering of large-scale high-dimensional data
    Jaegul Choo, Hanseung Lee, Zhicheng Liu, John Stasko, and Haesun Park
    Proc. SPIE 8654, Visualization and Data Analysis (VDA), pages 1-15, 2013
    [PDF][VIDEO][WEBSITE]
  • Fast Interactive Visualization for Multivariate Data Exploration
    Changhyun Lee, Wei Zhuo, Jaegul Choo, Duen Horng (Polo) Chau
    ACM SIGCHI Work-in-progress (CHI-WIP), 2013
    [PDF]
  • Augmenting MATLAB with Semantic Objects for an Interactive Visual Environment
    Changhyun Lee, Jaegul Choo, Haesun Park, and Duen Horng (Polo) Chau
    ACM SIGKDD Workshop on KDD 2013 Workshop on Interactive Data Exploration and Analytics (KDD-IDEA), 2013
    [PDF]
  • Lytic: Synthesizing High-Dimensional Algorithmic Analysis with Domain-Agnostic, Faceted Visual Analytics
    Edward Clarkson, Jaegul Choo, John Turgeson, Ray Decuir, and Haesun Park
    ACM SIGKDD Workshop on KDD 2013 Workshop on Interactive Data Exploration and Analytics (KDD-IDEA), 2013
    [PDF]
  • CiteVis: Exploring Conference Paper Citation Data Visually
  • John Stasko, Jaegul Choo, Yi Han, Mengdie Hu, Hannah Pileggi, Ramik Sadana, and Charles D. Stolper
    IEEE Conference on Information Visualization (InfoVis-Poster), 2013
    [PDF]
  • Augmenting MATLAB with Semantic Objects for an Interactive Visual Environment
    Changhyun Lee, Jaegul Choo, Haesun Park, and Duen Horng (Polo) Chau
    IEEE International Conference on Data Mining (Demo Paper) (ICDM-Demo), 2013
    [PDF]

2012

  • Heterogeneous Data Fusion via Space Alignment Using Nonmetric Multidimensional Scaling
    Jaegul Choo, Shawn Bohn, Grant C. Nakamura, Amanda M. White, and Haesun Park
    SIAM International Conference on Data Mining (SDM), pages 177-188, 2012
    [PDF]
  • iVisClustering: An Interactive Visual Clustering for Documents via Topic Modeling
    Hanseung Lee, Jaeyeon Kihm, Jaegul Choo, John Stasko, and Haesun Park
    Computer Graphics Forum (CGF), Volume 31, Issue 3pt3, pages 1155-1164, 2012
    [PDF][VIDEO]

2011

  • A Visual Analytics Approach for Protein Disorder Prediction
    Jaegul Choo, Fuxin Li, and Haesun Park
    Expanding the Frontiers of Visual Analytics and Visualization, pages 163-174, 2011
    [PDF]

2010

  • iVisClassifier: An Interactive Visual Analytics System for Classification based on Supervised Dimension Reduction
    Jaegul Choo, Hanseung Lee, Jaeyeon Kihm, and Haesun Park
    IEEE Conference on Visual Analytics Science and Technology (VAST), pages 27-34, 2010
    [PDF]
  • Data Ingestion and Evidence Marshalling in Jigsaw
    Zhicheng Liu, Carsten Görg, Jaeyeon Kihm, Hanseung Lee, Jaegul Choo, Haesun Park, and John Stasko
    IEEE Conference on Visual Analytics Science and Technology (VAST Challenge), pages 271-272, 2010
    [PDF]
  • GeneTracer: Gene Sequence Analysis of Disease Mutations
    Hanseung Lee, Jaegul Choo, Carsten Görg, Jaeeun Shim, Jaeyeon Kihm, Zhicheng Liu, Haesun Park, and John Stasko
    IEEE Conference on Visual Analytics Science and Technology (VAST Challenge), pages 291-292, 2010
    [PDF]
  • Combining Computational Analyses and Interactive Visualization to Enhance Information Retrieval
    Carsten Görg, Jaeyeon Kihm, Jaegul Choo, Zhicheng Liu, Sivasailam Muthiah, Haesun Park, and John Stasko
    4th Workshop on Human-Computer Interaction and Information Retrieval (HCIR), 2010
    [PDF]
  • p-ISOMAP: An Efficient Parametric Update for ISOMAP for Visual Analytics
    Jaegul Choo, Chandan K. Reddy, Hanseung Lee, and Haesun Park
    SIAM International Conference on Data Mining (SDM), pages 502-513, 2010
    [PDF]

2009

  • Two-stage Framework for Visualization of Clustered High Dimensional Data
    Jaegul Choo, Shawn Bohn, and Haesun Park
    IEEE Conference on Visual Analytics Science and Technology (VAST), pages 67-74, 2009
    [PDF]
  • Timeline analysis of undercover activities
    Jaegul Choo, Emily Fujimoto, Hanseung Lee, and Pedro R. Walteros
    IEEE Conference on Visual Analytics Science and Technology (VAST Challenge), pages 245-246, 2009
    [PDF]
  • Hierarchical Linear Discriminant Analysis for Beamforming
    Jaegul Choo, Barry L. Drake, and Haesun Park
    SIAM International Conference on Data Mining (SDM), pages 894-905, 2009
    [PDF]

2008

  • Linear Discriminant Analysis for Data with Subcluster Structure
    Haesun Park, Jaegul Choo, Barry L. Drake, and Jinwoo Kang
    International Conference on Pattern Recognition (ICPR), pages 1-4, 2008
    [PDF]

2007

  • A Comparison of Unsupervised Dimension Reduction Algorithms for Classification
    Jaegul Choo, Hyunsoo Kim, Haesun Park, and Hongyuan Zha
    IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pages 71-77, 2007
    [PDF]

Grants

  • Co-PI. Fast Algorithms on Imperfect, Heterogeneous, Distributed Data for Interactive Analysis
    PIs: Richard Fujimoto, Haesun Park, Hongyuan Zha
    Defense Advanced Research Projects Agency, XDATA Program
    $2.7M, September 2012 - February 2017.