My research interests are in machine learning and data mining. In particular, I study probabilistic Bayesian topic models which aims to discover latent patterns such as topics in unannotated data, and efficient inference methods of it for handling large corpus.
- KAIST, Ph.D., Computer Science, Mar 2013 - Present
- KAIST, M.S., Computer Science, Feb 2011 - Feb 2013
Thesis : Distributed Online Learning for Topic Models
- Sungkyunkwan University, B.S., Computer Engineering, Mar 2004 - Feb 2011
JinYeong Bak and Alice Oh. Conversational decision-making model for predicting the kings decision in the annals of the joseon dynasty. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, 2018.
[PDF] [Code and Data]
Sungjoon Park, JinYeong Bak, and Alice Oh. Rotated word vector representations andtheir interpretability. In Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, pages 401–411, 2017.
Jongin Lee, Daeki Cho, Junhong Kim, Eunji Im, JinYeong Bak, Kwan Hong Lee, John Kim, and others. Itchtector: A wearable-based mobile system for managing itching conditions. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, pages 893–905. ACM, 2017. Information Retrieval, 2017
JinYeong Bak Imaduddin Amin, Jong Gun Lee, and Alice Oh. Keyword expansion for understanding crisis events in indonesian tweets. In ICML Workshop on Interactive MachineLearning and Semantic Information Retrieval, 2017
JinYeong Bak and Alice Oh. Five centuries of monarchy in korea: Mining the text of the annals of the joseon dynasty. In Proceedings of the 9th SIGHUM Workshop on Language Technology for Cultural Heritage, Social Sciences, and Humanities (LaTeCH), pages 10–14, Beijing, China, July 2015. Association for Computational Linguistics
JinYeong Bak, Chin-Yew Lin, and Alice Oh. Self-disclosure topic model for classifying and analyzing twitter conversations. In Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing, 2014.
[PDF] [Code and Data] [Slides]
JinYeong Bak, Dongwoo Kim, and Alice Oh. Distributed online learning for latent dirichlet allocation. In Proceedings of Workshop on Big Learning : Algorithms, Systems, and Tools at the Neural Information Processing Systems, 2012
[PDF] [Supplementary] [Code and Data]
JinYeong Bak, Suin Kim, and Alice Oh. Self-disclosure and relationship strength in twitter conversations. In Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics, 2012.
Suin Kim, JinYeong Bak, and Alice Oh. Do you feel what i feel? social aspects of emotions in twitter conversations. In Proceedings of the AAAI International Conference on Weblogs and Social Media, 2012.
[PDF] [4-Page Poster] [Poster for 4-page paper]
- Research Intern, Microsoft Research Asia, Beijing, China, Sep 2013 - Feb 2014
:I interned with Chin-Yew Lin in the Knowledge Mining group at Microsoft Research Asia. I developed a topic model to identify self-disclosure in Twitter conversations. This work is published at EMNLP 2014 as full paper.
- Junior Data Scientist, United Nations Global Pulse Lab Jakarta, Jakarta, Indonesia, June 2016 - Aug 2016
: I interned with Jonggun Lee in the United Nations Global Pulse Lab Jakarta. I developed a topic model based methodology for expanding relevant keywords for specific subjects to identify related tweets in Twitter. This work is not published yet.
Reviewer and Program Committee
- The Annual Meeting of the Association for Computational Linguistics: 2015, 2016, 2017, 2018, 2019
- Conference on Empirical Methods in Natural Language Processing: 2015, 2016
- International AAAI Conference on Web and Social Media: 2015, 2016
- Language Technology for Cultural Heritage, Social Sciences, and Humanities: 2016, 2017, 2018, 2019
- THE WEB CONFERENCE: 2019
- Distributed online topic modeling for big data analysis. Samsung Electronics, Dec 2012 - Nov 2013
: I worked with the DMC group in Samsung Electronics. I developed online learning algorithms on Hadoop and implemented it in Java and Python.
- Machine Learning Center. Korean Government, Mar 2013 - June 2017
: I developed online learning algorithms for topic models on Apache Spark.
- Explainable Human-level Deep Machine Learning. Korean Government, Sep 2017 -
: I develop the explainable human-level Bayesian and deep learning algorithms.
- April - June 2017 and June - July 2018, Lecturer for Machine Learning, Elice
- Spring/Fall 2017, Spring/Fall 2016, Fall 2015, Spring/Fall 2014, Teaching Assistant for Introduction to Programming, KAIST
- Spring 2015, Spring 2013, Fall 2011, Teaching Assistant for Artificial Intelligence and Machine Learning, KAIST
- Fall 2010, Teaching Assistant for Operating Systems, Sungkyunkwan University
- Spring 2010, Teaching Assistant for Discrete mathematics, Sungkyunkwan University
- 2013.08.22. Bayesian Nonparametric Topic Modeling, Korean machine learning summer school, Seoul, South Korea
- 2014.10.23. Self-disclosure in Twitter conversations, Qatar Computing Research Institute, Doha, Qatar
- Student volunteer, 2018 Conference on Empirical Methods in Natural Language Processing (EMNLP2018), Oct 2018
- Students representative, Department of Computer Science, KAIST, 2014
- Student volunteer, Annual Meeting of the Association for Computational Linguistics 2012 (ACL 2012), July 2012
- Social service personnel, Banyeo library, Haeundae-gu office, Busan, Korea, May 2005 - July 2007
- Member and representative, Linux and Open-source learned club "SKKULUG", Sungkyunkwan Uni- versity, 2004 - 2010
- Prof. Alice Haeyun Oh, Department of Computer Science, KAIST, firstname.lastname@example.org
- Dr. Chin-Yew Lin, Knowledge Mining Group, Microsoft Research Asia, email@example.com
- Dr. Jonggun Lee, United Nations Global Pulse Lab Jakarta, firstname.lastname@example.org
- Prof. Sang Gu Lee, Department of Mathematics, Sungkyunkwan University, email@example.com