Jaegul Choo (주재걸) [Short Bio] [CV]
Associate Professor
Kim Jaechul Graduate School of Artificial Intelligence, KAIST

Main Office: 291 Daehak-ro, N24 LG Innovation Hall, Room# 3109, Yuseong-gu, Daejeon 34141, South Korea
Seongnam Office: 8 Seongnam-daero 331 beon-gil, KINS Tower, Suite 1801, Bundang-gu, Seongnam-si, Gyeonggi 13558, South Korea
Office Phone No.: +82-42-350-1813
E-mail: jchoo@kaist.ac.kr
Meeting Request
: Schedule a meeting

Announcement

  • 대학원 지원을 고려하는 분들은 다음 문서를 참고해주세요: [FAQ]

  • I am looking for self-motivated Postdocs, prospective graduate students, and undergraduate students. If you're interested, send me an email with your full Curriculum Vitae and transcript.

Courses

  • [VIDEO] Spring 2019, COSE111: Math for Computer Science I (Linear Algebra)

  • [VIDEO] Spring 2019, AAA635: Data Mining

  • [VIDEO] Spring 2019, DFC609: Big Data Analysis Basics

  • [VIDEO] Fall 2018, COSE474: Deep Learning

  • [VIDEO] Fall 2018, AAA625: Numerical Linear Algebra

  • [VIDEO] Fall 2018, DFE606: Big Data Analysis Basics

  • [VIDEO] Spring 2018, COSE111: Math for Computer Science I (Linear Algebra)

  • [VIDEO] Spring 2018, AAA606: Natural Language Processing Applications

  • [VIDEO] Spring 2018, DFC609: Big Data Analysis Basics

  • [VIDEO] Fall 2017, COSE492: Deep Learning

  • [VIDEO] Fall 2017, COSE112: Math for Computer Science II (Probability and Statistics)

  • [VIDEO] Fall 2017, CVH109: Big Data and Information Retrieval

  • [VIDEO] Fall 2017, DFE606: Big Data Analysis Basics

  • [VIDEO] Spring 2017, COSE111: Math for Computer Science I (Linear Algebra)

  • [VIDEO] Spring 2017, AAA638: Visual Analytics

  • [VIDEO] Spring 2017, CVH126: Data Science

  • [VIDEO] Fall 2016, COSE112: Math for Computer Science II (Probability and Statistics)

  • [VIDEO] Fall 2016, AAA625: Numerical Linear Algebra

  • [VIDEO] Spring 2016, COSE111: Math for Computer Science I (Linear Algebra)

  • Spring 2016, CRE653: Data Mining

  • Fall 2015, COSE472: Information Retrieval

  • Fall 2015, AAA638: Visual Analytics

  • Spring 2015, COSE111: Math for Computer Science I (Linear Algebra)

  • Spring 2015, CRE653: Data Mining

Research Interest

  • Visual analytics for user-driven machine learning and deep learning

  • Deep learning for reading comprehension-based question answering

  • Image generation and translation via generative adversarial networks

  • Deep learning for program debugging and auto-completion

  • Social media analysis and text mining

  • Web and user log mining

  • Large-scale interactive 2D embedding using t-SNE

  • Nonnegative matrix factorization (NMF) for clustering and topic modeling

Awards

Selected Publications [Google Scholar]

2021

  • AVocaDo: Strategy for Adapting Vocabulary to Downstream Domain
    Jimin Hong,* TaeHee Kim,* Hyesu Lim,* and Jaegul Choo (*: equal contributions)
    Conference on Empirical Methods in Natural Language Processing (
    EMNLP), Short Paper, 2021, Accepted.

  • Novel Natural Language Summarization of Program Code via Leveraging Multiple Input Representations
    Fuxiang Chen, Mijung Kim, and Jaegul Choo
    Conference on Empirical Methods in Natural Language Processing (
    EMNLP), Findings of EMNLP, 2021, Accepted.

  • Standardized Max Logit: A Simple yet Effective Approach for Identifying Unexpected Road Obstacles in Urban-scene Segmentation
    Sanghun Jung,* Jungsoo Lee,* Daehoon Gwak, Sungha Choi, and Jaegul Choo (*: equal contributions)
    International Conference on Computer Vision (ICCV), 2021, Accepted as Oral Presentation (3% acceptance rate).

  • Deep Edge-Aware Interactive Colorization against Color-Bleeding Effects
    Eungyeup Kim,* Sanghyeon Lee,* Jeonghoon Park,* So Mi Choi, Choonghyun Seo, and Jaegul Choo (*: equal contributions)
    International Conference on Computer Vision (
    ICCV), 2021, Accepted as Oral Presentation (3% acceptance rate).

  • BiaSwap: Removing Dataset Bias with Bias-Tailored Swapping Augmentation
    Eungyeup Kim,* Jihyeon Lee,* and Jaegul Choo (*: equal contributions)
    International Conference on Computer Vision (
    ICCV), 2021, Accepted (25.9% acceptance rate).

  • Understanding Human-side Impact of Sampling Image Batches in Subjective Attribute Labeling
    Chaeyeon Chung,* Jungsoo Lee,* Kyungmin Park, Junsoo Lee, Minjae Kim, Mookyung Song, Yeonwoo Kim, Jaegul Choo, and Sungsoo Ray Hong (*: equal contributions)
    ACM Conference on Computer-Supported Cooperative Work and Social Computing (
    CSCW), 2021, Accepted.

  • Prediction of Hand-Wrist Maturation Stages based on Cervical Vertebrae Images using Artificial Intelligence
    Dong-Wook Kim,* Jinhee Kim,* Taesung Kim, Taewoo Kim, Yoon-Ji Kim, In-Seok Song, Byungduk Ahn, Jaegul Choo, and Dong-Yul Lee (*: equal contributions)
    Orthodontics & Craniofacial Research, 2021
    .
    [PDF]

  • Knowledge Graph-based Question Answering with Electronic Health Records
    Junwoo Park, Youngwoo Cho, Haneol Lee, Jaegul Choo, and Edward Choi
    Machine Learning for Healthcare (MLHC), 2021, Accepted.
    [PDF] [INTRO_TALK]

  • K-Hairstyle: A Large-Scale Korean Hairstyle Dataset for Virtual Hair Editing and Hairstyle Classification
    Taewoo Kim, Chaeyeon Chung, Sunghyun Park, Gyojung Gu, Keonmin Nam, Wonzo Choe, Jaesung Lee, and Jaegul Choo
    IEEE International Conference on Image Processing (ICIP), 2021.
    [PROJECT] [PDF]

  • Unsupervised Neural Machine Translation for Low-Resource Domains via Meta-Learning
    Cheonbok Park,* Yunwon Tae,* TaeHee Kim, Soyoung Yang, Mohammad Azam Khan, Lucy Park, and Jaegul Choo (*: equal contributions)
    Joint Conference of the Annual Meeting of the Association for Computational Linguistics and the International Joint Conference on Natural Language Processing (ACL-IJCNLP), Long Paper, 2021.
    [PDF]

  • Constructing Multi-Modal Dialogue Dataset by Replacing Text with Semantically Relevant Images
    Nyoungwoo Lee,* Suwon Shin,* Jaegul Choo, Ho-Jin Choi, and Sung-Hyon Myaeng (*: equal contributions)
    Joint Conference of the Annual Meeting of the Association for Computational Linguistics and the International Joint Conference on Natural Language Processing (ACL-IJCNLP), Short Paper, 2021, Accepted.
    [PROJECT] [PDF]

  • Learning to Generate Questions by Learning to Recover Answer-containing Sentences
    Seohyun Back, Akhil Kedia, Sai Chetan Chinthakindi, Haejun Lee, and Jaegul Choo
    Joint Conference of the Annual Meeting of the Association for Computational Linguistics and the International Joint Conference on Natural Language Processing (ACL-IJCNLP), Findings of ACL, 2021,.
    [PDF]

  • VATUN: Visual Analytics for Testing and Understanding Convolutional Neural Networks
    Cheonbok Park,* Soyoung Yang,* Inyoup Na,* Sunghyo Chung, Sungbok Shin, Bum Chul Kwon, Deokgun Park, and Jaegul Choo (*: equal contributions)
    EG/VGTC Conference on Visualization (EuroVis), Short Paper, 2021.
    [PDF] [DEMO] [TALK]

  • Artificial Intelligence-Assisted Analysis of Endoscopic Retrograde Cholangiopancreatography Image for Identifying Ampulla and Difficulty of Selective Cannulation
    Taesung Kim,* Jinhee Kim,* Hyuk Soon Choi, Eun Sun Kim, Bora Keum, Yoon Tae Jeen, Hong Sik Lee, Hoon Jai Chun, Sung Yong Han, Dong Uk Kim, Soonwook Kwon, Jaegul Choo, and Jae Min Lee (*: equal contributions)
    Scientific Reports, 2021.
    [PDF]

  • Restoring and Mining the Records of the Joseon Dynasty via Neural Language Modeling and Machine Translation
    Kyeongpil Kang, Kyohoon Jin, Soyoung Yang, Soojin Jang, Jaegul Choo, and YoungBin Kim
    Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), 2021.
    [PDF]

  • 3D Cell Instance Segmentation via Point Proposals using Cellular Components
    Jinho Choi, Junwoo Park, Hyungjoo Cho, Hyeonseok Min, Sungbin Lim, and Jaegul Choo
    Proc. SPIE 11647, Imaging, Manipulation, and Analysis of Biomolecules, Cells, and Tissues XIX
    [PDF]

  • RobustNet: Improving Domain Generalization in Urban-Scene Segmentation via Instance Selective Whitening
    Sungha Choi,* Sanghun Jung,* Huiwon Yun, Joanne Kim, Seungryong Kim, and Jaegul Choo (*: equal contributions)
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021, Accepted as Oral Presentation (4.7% acceptance rate).
    [PDF] [TALK] [CODE]

  • VITON-HD: High-Resolution Virtual Try-On via Misalignment-Aware Normalization
    Seunghwan Choi,* Sunghyun Park,* Minsoo Lee,* and Jaegul Choo (*: equal contributions)
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021 (27% acceptance rate).
    [PDF] [DEMO] [CODE]

  • Not Just Compete, but Collaborate: Local Image-to-Image Translation via Cooperative Mask Prediction
    Daejin Kim, Mohammad Azam Khan, and Jaegul Choo
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021 (27% acceptance rate).
    [PDF]

  • An Empirical Experiment on Deep Learning Models for Predicting Traffic Data
    Hyunwook Lee, Cheonbok Park, Seungmin Jin, Hyeshin Chu, Jaegul Choo, and Sungahn Ko
    IEEE International Conference on Data Engineering (ICDE), Short Paper, 2021.
    [PDF]

  • Efficient Adversarial Audio Synthesis via Progressive Upsampling
    Youngwoo Cho, Minwook Chang, Sanghyeon Lee, Hyoungwoo Lee, Gerard Jounghyun Kim, and Jaegul Choo
    IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021 (48.0% acceptance rate).
    [PDF]

  • Development of Artificial Intelligence System for Quality Control of Photo Documentation in Esophagogastroduodenoscopy
    Seong Ji Choi,* Mohammad Azam Khan,* Hyuk Soon Choi, Jaegul Choo, Jae Min Lee, and Soonwook Kwon (*: equal contributions)
    Surgical Endoscopy, 2021 (IF: 3.149, as of 2019).
    [PDF]

  • Vid-ODE: Continuous-Time Video Generation with Neural Ordinary Differential Equation
    Sunghyun Park,* Kangyeol Kim,* Junsoo Lee, Jaegul Choo, Joonseok Lee, Sookyung Kim, and Edward Choi (*: equal contributions)
    AAAI Conference on Artificial Intelligence (AAAI), 2021 (21.4% acceptance rate).
    [PDF] [CODE]

2020

  • End-To-End Multi-Task Learning of Missing Value Imputation and Forecasting in Time-Series Data
    Jinhee Kim,* Taesung Kim,* Jang-Ho Choi, and Jaegul Choo (*: equal contributions)
    International Conference on Pattern Recognition (ICPR), 2020.
    [PDF]

  • HyperTendril: Visual Analytics for User-Driven Hyperparameter Optimization of Deep Neural Networks
    Heungseok Park, Yoonsoo Nam, Ji-Hoon Kim, and Jaegul Choo
    IEEE Trans. on Visualization and Computer Graphics (TVCG), 2021 (Proc. IEEE VIS'20) (24.8% acceptance rate).
    [PROJECT] [PDF]

  • Multimodal Image Translation with Stochastic Style Representations and Mutual Information Loss
    Sanghyeon Na, Seungjoo Yoo, and Jaegul Choo
    British Machine Vision Conference (BMVC), 2020, Accepted as Oral Presentation (5.0% acceptance rate for oral-presentation papers).
    [PDF]

  • ST-GRAT: A Novel Spatio-temporal Graph Attention Networks for Accurately Forecasting Dynamically Changing Road Speed
    Cheonbok Park, Chunggi Lee, Hyojin Bahng, Yunwon Tae, Seungmin Jin, Kihwan Kim, Sungahn Ko, and Jaegul Choo
    ACM International Conference on Information and Knowledge Management (CIKM), 2020 (20.9% acceptance rate).
    [PDF]

  • Learning De-biased Representations with Biased Representations
    Hyojin Bahng, Sanghyuk Chun, Sangdoo Yun, Jaegul Choo, and Seong Joon Oh
    International Conference on Machine Learning (ICML), 2020 (21.8% acceptance rate).
    [PDF] [CODE] [TALK]

  • Automatic Detection of Tympanic Membrane and Middle Ear Infection from Oto-Endoscopic Images via Convolutional Neural Networks
    Mohammad Azam Khan,* Soonwook Kwon,* Jaegul Choo, Seok Min Hong, Sung Hun Kang, Il-Ho Park, Sung Kyun Kim, and Seok Jin Hong (*: equal contributions)
    Neural Networks (IF: 5.875, as of 2018), 2020.
    [PDF]

  • Cars Can’t Fly Up in the Sky: Improving Urban-Scene Segmentation via Height-driven Attention Networks
    Sungha Choi, Joanne Kim, and Jaegul Choo
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020, Seattle, WA (22.1% acceptance rate).
    [PDF] [INTRO_VIDEO] [CODE]

  • Reference-based Sketch Image Colorization using Augmented-Self Reference and Dense Semantic Correspondence
    Junsoo Lee, Eungyeup Kim, Yunsung Lee, Dongjun Kim, Jaehyuk Chang, and Jaegul Choo
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020, Seattle, WA (22.1% acceptance rate).
    [PDF]

  • Exploring Unlabeled Faces for Novel Attribute Discovery
    Hyojin Bahng, Sunghyo Chung, Seungjoo Yoo, and Jaegul Choo
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020, Seattle, WA (22.1% acceptance rate).
    [PDF]

  • NeurQuRI: Neural Question Requirement Inspector for Answerability Prediction in Machine Reading Comprehension
    Seohyun Back, Sai Chetan Chinthakindi, Akhil Kedia, Haejun Lee, and Jaegul Choo
    International Conference on Learning Representations (ICLR), 2020, Addis Ababa, Ethiopia (26.5% acceptance rate).
    [PDF]

  • Probabilistic Topic Modeling for Comparative Analysis of Document Collections
    Ting Hua, Chang-Tien Lu, Jaegul Choo, and Chandan K. Reddy
    ACM Transactions on Knowledge Discovery from Data (TKDD), 2020.
    [PDF]

2019

  • NL2pSQL: Generating Pseudo-SQL Queries from Under-Specified Natural Language Questions
    Fuxiang Chen, Seung-won Hwang, Jaegul Choo, Jung-Woo Ha, and Sunghun Kim
    Conference on Empirical Methods in Natural Language Processing (EMNLP), 2019, Hong Kong, Accepted as Long Paper (23.8% acceptance rate).
    [PDF]

  • Recommender System Using Sequential and Global Preference via Attention Mechanism and Topic Modeling
    Kyeongpil Kang, Junwoo Park, Wooyoung Kim, Hojung Choe, and Jaegul Choo
    ACM International Conference on Information and Knowledge Management (CIKM), 2019, Beijing, China, Accepted as Full Paper (19% acceptance rate).
    [PDF]

  • SANVis: Visual Analytics for Understanding Self-Attention Networks
    Cheonbok Park, Inyoup Na, Yongjang Jo, Sungbok Shin, Jaehyo Yoo, Bum Chul Kwon, Jian Zhao, Hyungjong Noh, Yeonsoo Lee, and Jaegul Choo
    IEEE VIS, Short Paper, 2019, Vancouver, Canada (31.7% acceptance rate).
    [PDF] [YOUTUBE]

  • Learning to Focus and Track Extreme Climate Events
    Sookyung Kim,* Sunghyun Park,* Sunghyo Chung,* Joonseok Lee, Yunsung Lee, Hyojin Kim, Mr Prabhat, and Jaegul Choo
    British Machine Vision Conference (BMVC), 2019, Cardiff, UK, Accepted as Spotlight Presentation (6.9% acceptance rate for spotlight papers).
    [PDF] [SLIDE]

  • Whose Opinion Matters? Analyzing Relationships between Bitcoin Prices and User Groups in Online Community
    Kyeongpil Kang, Jaegul Choo, and YoungBin Kim
    Social Science Computer Review (IF: 3.253), 2019
    [PDF]

  • Image-to-Image Translation via Group-wise Deep Whitening and Coloring
    Wonwoong Cho, Sungha Choi, David Park, Inkyu Shin, and Jaegul Choo
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019, Long Beach, CA, Accepted as Oral Presentation (5.5% acceptance rate for oral-presentation papers).
    [PDF] [TALK]

  • Coloring with Limited Data: Few-Shot Colorization via Memory-Augmented Networks
    Seungjoo Yoo, Hyojin Bahng, Sunghyo Chung, Junsoo Lee, Jaehyuk Chang, and Jaegul Choo
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019, Long Beach, CA (25.2% acceptance rate).
    [PROJECT] [PDF]

  • Visualizing for the Non-Visual: Deep Learning to Enable Visually Impaired to Use Visualization
    Jinho Choi, SangHun Jung, Deokgun Park, Jaegul Choo, and Niklas Elmqvist
    Computer Graphics Forum (CGF), 2019 (Proc. EuroVis'19), Porto, Portugal.
    [PDF] [BLOG ARTICLE]

  • AILA: Attentive Interactive Labeling Assistant for Document Classification through Attention-based Deep Neural Networks
    Minsuk Choi, Cheonbok Park, Soyoung Yang, Yonggyu Kim, Jaegul Choo, and Sungsoo (Ray) Hong
    ACM CHI Conference on Human Factors in Computing Systems (CHI), 2019, Glasgow, UK (23.8% acceptance rate).
    [PDF] [INTRO_VIDEO] [VIDEO]

  • Paraphrase Diversification using Counterfactual Debiasing
    Sunghyun Park, Seung-won Hwang, Fuxiang Chen, Jaegul Choo, Jung-Woo Ha, Sunghun Kim, and Jinyeong Yim
    AAAI Conference on Artificial Intelligence (AAAI), 2019, Honolulu, HI (16.2% acceptance rate).
    [PDF]

2018

  • MemoReader: Large-Scale Reading Comprehension through Neural Memory Controller
    Seohyun Back, Seunghak Yu, Sathish Reddy Indurthi, Jihie Kim, and Jaegul Choo
    Conference on Empirical Methods in Natural Language Processing (EMNLP), 2018, Brussels, Belgium, Long paper.
    [PDF]

  • Guidance in the human-machine analytics process
    Christopher Collins, Natalia Andrienko, Tobias Schreck, Jing Yang, Jaegul Choo, Ulrich Engelke, Amit Jena, and Tim Dwyer
    Visual Informatics, 2018
    [PDF]

  • Coloring with Words: Guiding Image Colorization Through Text-based Palette Generation
    Hyojin Bahng,* Seungjoo Yoo,* Wonwoong Cho,* David K. Park, Ziming Wu, Xiaojuan Ma, and Jaegul Choo (*: equal contributions)
    European Conference on Computer Vision (ECCV), 2018, Munich, Germany (31.8% acceptance rate).
    [PDF] [CODE]

  • RetainVis: Visual Analytics with Interpretable and Interactive Recurrent Neural Networks on Electronic Medical Records
    Bum Chul Kwon, Min-Je Choi, Joanne Taery Kim, Edward Choi, Young Bin Kim, Soonwook Kwon, Jimeng Sun, and Jaegul Choo
    IEEE Trans. on Visualization and Computer Graphics (TVCG), 2019 (Proc. IEEE VIS'18) (25.6% acceptance rate).
    [PDF] [VIDEO] [WEBSITE]

  • MEGAN: Mixture of Experts of Generative Adversarial Networks for Multimodal Image Generation
    David K. Park, Seungjoo Yoo, Hyojin Bahng, Jaegul Choo, and Noseong Park
    International Joint Conference on Artificial Intelligence (IJCAI), 2018, Stockholm, Sweden (20.5% acceptance rate).
    [PDF]

  • MMGAN: Manifold-Matching Generative Adversarial Networks
    Noseong Park, Ankesh Anand, Joel Ruben, Antony Moniz, Kookjin Lee, Jaegul Choo, David. K. Park, Tanmoy Chakraborty, Hongkyu Park, and Youngmin Kim
    International Conference on Pattern Recognition (ICPR), 2018, Beijing, China.
    [PDF]

  • Visual Analytics for Explainable Deep Learning
    Jaegul Choo
    and Shixia Liu
    IEEE Computer Graphics and Applications (CG&A), Vol. 38, No. 4, pp. 84-92, Jul./Aug. 2018.
    [PDF]

  • StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation
    Yunjey Choi, Minje Choi, Munyoung Kim, Jung-Woo Ha, Sunghun Kim, and Jaegul Choo
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018, Salt Lake City, UT, Oral Presentation (2.1% acceptance rate for oral-presentation papers).
    [PDF] [CODE] [VIDEO]

  • PixelSNE: Pixel-Aligned Stochastic Neighbor Embedding for Efficient 2D Visualization with Screen-Resolution Precision
    Minjeong Kim, Minsuk Choi, Sunwoong Lee, Jian Tang, Haesun Park, and Jaegul Choo
    Computer Graphics Forum (CGF), 2018 (Proc. EuroVis'18), Brno, Czech Republic (29% acceptance rate).
    [PDF] [INTRO_VIDEO] [CODE]

  • Short-Text Topic Modeling via Non-negative Matrix Factorization Enriched with Local Word-Context Correlations
    Tian Shi, Kyeongpil Kang, Jaegul Choo, and Chandan K. Reddy
    International World Wide Web Conference (WWW), 2018, Lyon, France (15% acceptance rate).
    [PDF]

  • TopicOnTiles: Tile-based Spatio-Temporal Event Analytics via Exclusive Topic Modeling on Social Media
    Minsuk Choi, Sungbok Shin, Jinho Choi, Scott Langevin, Christopher Bethune, Philippe Horne, Nathan Kronenfeld, Ramakrishnan Kannan, Barry Drake, Haesun Park, and Jaegul Choo
    ACM CHI Conference on Human Factors in Computing Systems (CHI), 2018, Montréal, Canada (25.7% acceptance rate).
    [PDF] [INTRO_VIDEO] [VIDEO]

  • VisIRR: A Visual Analytics System for Information Retrieval and Recommendation for Large-Scale Document Data
    Jaegul Choo
    , Hannah Kim, Edward Clarkson, Zhiecheng Liu, Changhyun Lee, Fuxin Li, Hanseung Lee, Ramakrishnan Kannan, Charles D. Stolper, John Stasko, and Haesun Park
    ACM Transactions on Knowledge Discovery from Data (TKDD), Vol. 12, No. 8, pp. 1-20, 2018
    [PDF] [VIDEO]

  • ConceptVector: Text Visual Analytics via Interactive Lexicon Building Using Word Embedding
    Deokgun Park, Seungyeon Kim, Jurim Lee, Jaegul Choo, Nicholas Diakopoulos, and Niklas Elmqvist
    IEEE Trans. on Visualization and Computer Graphics (TVCG), Vol. 24, No. 1, pp. 361-370, 2018 (Proc. IEEE VIS'17) (21% acceptance rate).
    [PDF] [YOUTUBE] [TALK] [DEMO]

  • Localized User-Driven Topic Discovery via Boosted Ensemble of Nonnegative Matrix Factorization
    Sangho Suh, Sungbok Shin, Joonseok Lee, Chandan K. Reddy, and Jaegul Choo
    Knowledge and Information Systems (KAIS), Vol. 56, No. 3, pp. 503-531, 2018
    [PDF]

2017

  • Consistent Comic Colorization with Pixel-wise Background Classification
    Sungmin Kang, Jaegul Choo, and Jaehyuk Chang
    NIPS'17 Workshop on Machine Learning for Creativity and Design, 2017
    [PDF]

  • Predicting the Currency Market in Online Gaming via Lexicon-based Analysis on Its Online Forum
    Young Bin Kim, Kyeongpil Kang, Jaegul Choo, Shin Jin Kang, TaeHyeong Kim, JaeHo Im, Jong-Hyun Kim, and Chang Hun Kim
    Complexity (IF=4.621), 2017
    [PDF]

  • STExNMF: Spatio-Temporally Exclusive Topic Discovery for Anomalous Event Detection
    Sungbok Shin, Minsuk Choi, Jinho Choi, Scott Langevin, Christopher Bethune, Philippe Horne, Nathan Kronenfeld, Ramakrishnan Kannan, Drake Barry, Haesun Park, and Jaegul Choo
    IEEE International Conference on Data Mining (ICDM), 2017, New Orleans, LA (9.2% acceptance rate for regular papers).
    [PDF]

  • Toward Predicting Social Support Needs in Online Health Social Networks
    Min-Je Choi, Sung-Hee Kim, Sukwon Lee, Bum Chul Kwon, Ji Soo Yi, Jaegul Choo, and Jina Huh
    Journal of Medical Internet Research (JMIR), Vol. 19, No. 8: e272, 2017
    [PDF]

  • Local Topic Discovery via Boosted Ensemble of Nonnegative Matrix Factorization
    Sangho Suh, Jaegul Choo, Joonseok Lee, and Chandan K. Reddy
    International Joint Conference on Artificial Intelligence (IJCAI), 2017, Melbourne, Australia, Invited to Best Sister Conferences Paper Track as the ICDM'16 Best Student Paper.
    [PDF]

  • End-to-End Prediction of Buffer Overruns from Raw Source Code via Neural Memory Networks
    Min-Je Choi, Sehun Jeong, Hakjoo Oh, and Jaegul Choo
    International Joint Conference on Artificial Intelligence (IJCAI), 2017, Melbourne, Australia (26% acceptance rate)
    [PDF]

  • When Bitcoin Encounters Information in an Online Forum: Using Text Mining to Analyse User Opinions and Predict Value Fluctuation
    Young Bin Kim, Jurim Lee, Nuri Park, Jaegul Choo, Jong-Hyun Kim, and Chang Hun Kim
    PLoS ONE, Vol. 12, No. 5, pp. 1598-1621, 2017
    [PDF]

  • PIVE: Per-Iteration Visualization Environment for Real-Time Interactions with Dimension Reduction and Clustering
    Hannah Kim, Jaegul Choo, Changhyun Lee, Hanseung Lee, Chandan K. Reddy, and Haesun Park
    AAAI Conference on Artificial Intelligence (AAAI), 2017, San Francisco, CA (25% acceptance rate)
    [PDF] [VIDEO]

  • TopicLens: Efficient Multi-Level Visual Topic Exploration of Large-Scale Document Collections
    Minjeong Kim, Kyeongpil Kang, Deokgun Park, Jaegul Choo, and Niklas Elmqvist
    IEEE Trans. on Visualization and Computer Graphics (TVCG), Vol. 23, No. 1, pp. 151-160, 2017 (Proc. IEEE VIS'16) (21% acceptance rate)
    [PDF] [VIDEO] [TALK]

  • AxiSketcher: Interactive Nonlinear Axis Mapping of Visualizations through User Drawings
    Bum Chul Kwon, Hannah Kim, Emily Wall, Jaegul Choo, Haesun Park, and Alex Endert
    IEEE Trans. on Visualization and Computer Graphics (TVCG), Vol. 23, No. 1, pp. 221-230, 2017 (Proc. IEEE VIS'16) (21% acceptance rate)
    [PDF] [VIDEO] [TALK]

  • High-Recall Document Retrieval from Large-Scale Noisy Documents via Visual Analytics based on Targeted Topic Modeling
    Hannah Kim, Jaegul Choo, Alex Endert, and Haesun Park
    IEEE Conference on Visual Analytics Science and Technology (VAST), 2017, Phoenix, AZ (Poster paper)
    [PDF] [VIDEO]

2016

  • L-EnsNMF: Boosted Local Topic Discovery via Ensemble of Nonnegative Matrix Factorization
    Sangho Suh, Jaegul Choo, Joonseok Lee, and Chandan K. Reddy
    IEEE International Conference on Data Mining (ICDM), 2016, Barcelona, Spain (8.5% acceptance rate for regular papers), BEST STUDENT PAPER AWARD
    [PDF] [SLIDE] [CODE]

  • Personas in Online Health Communities
    Jina Huh, Bum Chul Kwon, Sung-Hee Kim, Sukwon Lee, Jaegul Choo, Jihoon Kim, Min-Je Choi, and Ji Soo Yi
    Journal of Biomedical Informatics (JBI), Vol. 63, pp. 212-225, 2016
    [PDF]

  • InterAxis: Steering Scatterplot Axes via Observation-Level Interaction
    Hannah Kim, Jaegul Choo, Haesun Park, and Alex Endert
    IEEE Trans. on Visualization and Computer Graphics (TVCG), Vol. 22, No. 1, pp. 131-140, 2016 (Proc. IEEE VIS'15) (22% acceptance rate)
    [PDF] [SLIDE] [INTRO_VIDEO] [VIDEO]

  • VisOHC: Designing Visual Analytics for Online Health Communities
    Bum Chul Kwon, Sung-Hee Kim, Sukwon Lee, Jaegul Choo, Jina Huh, and Ji Soo Yi
    IEEE Trans. on Visualization and Computer Graphics (TVCG), Vol. 22, No. 1, pp. 71-80, 2016 (Proc. IEEE VIS'15) (22% acceptance rate)
    [PDF] [INTRO_VIDEO] [VIDEO]

  • ReVACNN: Real-Time Visual Analytics for Convolutional Neural Network
    Sunghyo Chung, Sangho Suh, Cheonbok Park, Kyeongpil Kang, Jaegul Choo, and Bum Chul Kwon
    ACM SIGKDD Workshop on Interactive Data Exploration and Analytics (KDD-IDEA), 2016, San Francisco, CA
    [PDF]

  • Tile-based Spatio-Temporal Visual Analytics via Topic Modeling on Social Media
    Minsuk Choi, Jaeseong Yoo, Ashley S. Beavers, Scott Langevin, Chris Bethune, Sean McIntyre, Barry L. Drake, Jaegul Choo, and Haesun Park
    IEEE Conference on Visual Analytics Science and Technology (VAST), 2016, Baltimore, MD (Poster paper)
    [PDF]

2015

  • 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), Vol. 29, No. 6, pp. 1598-1621, 2015
    [PDF]

  • Doubly Supervised Embedding based on Class Labels and Intrinsic Clusters for High-Dimensional Data Visualization
    Hannah Kim, Jaegul Choo, Chandan K. Reddy, and Haesun Park
    Neurocomputing, Vol. 150, Part B, No. 12, pp. 570-582, 2015
    [PDF]

  • Simultaneous Discovery of Common and Discriminative Topics via Joint Nonnegative Matrix Factorization
    Hannah Kim, Jaegul Choo, Jingu Kim, Chandan K. Reddy, and Haesun Park
    ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2015, Sydney, Australia (19% acceptance rate)
    [PDF] [SLIDE]

  • Project Recommendation Using Heterogeneous Traits in Crowdfunding
    Vineeth Rakesh, Jaegul Choo, and Chandan K. Reddy
    International AAAI Conference on Web and Social Media (ICWSM), 2015, Oxford, UK (19% acceptance rate)
    [PDF]

  • DemographicVis: Analyzing Demographic Information based on User Generated Content
    Wenwen Dou, Isaac Cho, Omar ElTayeby, Jaegul Choo, Derek Xiaoyu Wang, and William Ribarsky
    IEEE Conference on Visual Analytics Science and Technology (VAST), 2015, Chicago, Il
    [PDF] [YOUTUBE]

  • Nonnegative Matrix Factorization for Interactive Topic Modeling and Document Clustering
    Da Kuang, Jaegul Choo, and Haesun Park
    Partitional Clustering Algorithms, pp. 215-243, Springer, 2015 (Book chapter)
    [PDF]

  • Opinion Marks: A Human-based Computation Approach to Instill Structure into Unstructured Text on the Web
    Bum Chul Kwon, Jaegul Choo, Sung-Hee Kim, Daniel Keim, Haesun Park, and Ji Soo Yi
    ACM SIGKDD Workshop on Interactive Data Exploration and Analytics (KDD-IDEA), 2015, Sydney, Australia
    [PDF]

2014

  • 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 World Wide Web Conference (WWW), 2014, Seoul, Korea
    [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), 2014, New York, NY
    [PDF] [SLIDE]

  • PIVE: Per-Iteration Visualization Environment for Supporting Real-Time Interactions with Computational Methods
    Jaegul Choo
    , Changhyun Lee, Hannah Kim, Hanseung Lee, Barry L. Drake, and Haesun Park
    IEEE Conference on Visual Analytics Science and Technology (VAST), 2014, Paris, France (Poster paper), BEST POSTER AWARD
    [PDF] [INTRO_VIDEO] [VIDEO]

  • 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), 2014, Paris, France (Poster paper
    [PDF] [INTRO_VIDEO] [VIDEO]

  • Exploring Anomalies in GAStech: VAST Mini Challenge 1 and 2
    Jaegul Choo
    , Yi Han, Mengdie Hu, Hannah Kim, James Nugent, Francesco Poggi, Haesun Park, and John Stasko
    IEEE Conference on Visual Analytics Science and Technology Challenge (VAST Challenge), 2014, Paris, France (Poster paper)
    [PDF] [MC1_VIDEO] [MC2_VIDEO]

  • 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 (BIG), 2014, Seoul, Korea (Demo paper)
    [PDF]

2013

  • UTOPIAN: User-driven Topic Modeling based on Interactive Nonnegative Matrix Factorization
    Jaegul Choo
    , Changhyun Lee, Chandan K. Reddy, and Haesun Park
    IEEE Trans. on Visualization and Computer Graphics (TVCG), Vol. 19, No. 12, pp. 1992-2001, 2013 (Proc. IEEE VIS'13)
    [PDF] [SLIDE] [YOUTUBE]

  • Customizing Computational Methods for Visual Analytics with Big Data
    Jaegul Choo
    and Haesun Park
    IEEE Computer Graphics and Applications (CG&A), Vol. 33, Issue 4, pp. 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 Trans. on Visualization and Computer Graphics (TVCG), Vol. 19, No. 10, pp. 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), 2013, Burlingame, CA
    [PDF] [VIDEO] [WEBSITE]

  • Fast Interactive Visualization for Multivariate Data Exploration
    Changhyun Lee, Wei Zhuo, Jaegul Choo, Duen Horng (Polo) Chau, and Haesun Park
    ACM SIGCHI Work-in-progress (CHI-WIP), 2013, Paris, France
    [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 Interactive Data Exploration and Analytics (KDD-IDEA), 2013, Chicago, IL
    [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 Interactive Data Exploration and Analytics (KDD-IDEA), 2013, Chicago, IL
    [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), 2013, Atlanta, GA (Poster paper)
    [PDF] [WEBSITE]

  • 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 (ICDM), 2013, Dallas, TX (Demo paper)
    [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), 2012, Anaheim, CA
    [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), Vol. 31, Issue 3pt3, pp. 1155-1164, 2012 (Proc. EuroVis'12)
    [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, pp. 163-174, Springer, 2011 (Book chapter)
    [PDF]

2010

  • 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), 2010, Columbus, OH
    [PDF]

  • 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), 2010, Salt Lake City, UT
    [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 Challenge (VAST Challenge), 2010, Salt Lake City, UT (Poster paper)
    [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 Challenge (VAST Challenge), 2010, Salt Lake City, UT (Poster paper)
    [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, New Brunswick, NJ
    [PDF]

2009

  • Hierarchical Linear Discriminant Analysis for Beamforming
    Jaegul Choo
    , Barry L. Drake, and Haesun Park
    SIAM International Conference on Data Mining (SDM), 2009, Sparks, NV
    [PDF]

  • 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), 2009, Atlantic City, NJ
    [PDF]

  • Timeline analysis of undercover activities
    Jaegul Choo
    , Emily Fujimoto, Hanseung Lee, and Pedro R. Walteros
    IEEE Conference on Visual Analytics Science and Technology Challenge (VAST Challenge), 2009, Atlantic City, NJ (Poster paper)
    [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), 2008, Tampa, FL
    [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), 2007, Fremont, CA
    [PDF]