Hi, I'm a final-year computer science PhD student at Georgia Tech, advised by Polo Chau.
My research on "Human-Centered AI through Scalable Visual Data Analytics" focuses on building novel data visualization tools for helping people explore, interpret, and interact with machine learning systems, by combining methods from data visualization, machine learning, databases, data mining, and human-computer interaction.
My PhD studies have been supported by the Google PhD Fellowship and the NSF Graduate Research Fellowship. During my PhD studies, I have been fortunate to work with amazing people at Google Brain and Facebook Research, resulting in publications and open-sourced and deployed systems.
Prior to Georgia Tech, I completed both my master's and bachelor's degrees at Seoul National University in South Korea.
I'm currently on the faculty job market! Here are my application materials:
News
- Sept 2018 New paper, GAN Lab, accepted to IEEE VAST'18! Try our live system here!
- Aug 2018 Co-organized IDEA workshop at KDD 2018.
- May 2018 New survey paper on visual analytics for deep learning accepted to IEEE TVCG.
- Apr 2018 Thrilled to be awarded the Google PhD Fellowship!
- Apr 2018 Awarded the Graduate TA of the Year in School of Computer Science!
Research Highlights
Education
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Ph.D. Candidate in Computer Science,
Georgia Institute of Technology, USA
2013-2019
Thesis: Human-Centered AI through Scalable Visual Data Analytics
Committee: Polo Chau, Sham Navathe, Alex Endert, Martin Wattenberg, Fernanda Viégas -
M.S. in Computer Science and Engineering,
Seoul National University, South Korea
2009-2011
Thesis: Context-Aware Recommendation using Learning-to-Rank - B.S. in Electrical and Computer Engineering, Seoul National University, South Korea 2005-2009
Awards (selected)
- Google PhD Fellowship, Google AI 2018-2019
- Graduate TA of the Year in School of Computer Science, Georgia Tech Apr 2018
- NSF Graduate Research Fellowship, National Science Foundation 2014-2017
- Best Paper Award, PhD Workshop at CIKM Oct 2011
Industry Research Experience
- Google, Software Engineering Intern at Google Brain's People+AI Research Group Summer 2017
- Facebook, Research Intern at Applied ML Research Group Summer 2016
- Facebook, Research Intern at Applied ML Research Group Summer 2015
Selected Publications Full list (h-index: 13)
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GAN Lab: Understanding Complex Deep Generative Models using Interactive Visual Experimentation
IEEE Transactions on Visualization and Computer Graphics, 25(1) (VAST 2018), 2019.
Open sourced with Google AI
DOI PDF Slides Code Website -
Visual Analytics in Deep Learning: An Interrogative Survey for the Next Frontiers
IEEE Transactions on Visualization and Computer Graphics (Early Access).
DOI PDF Website -
ActiVis: Visual Exploration of Industry-Scale Deep Neural Network Models
IEEE Transactions on Visualization and Computer Graphics, 24(1) (VAST 2017), 2018.
Deployed by Facebook
DOI PDF Video Slides Website -
FACETS: Adaptive Local Exploration of Large Graphs
SIAM International Conference on Data Mining (SDM 2017), 2017.
DOI PDF -
Interactive Browsing and Navigation in Relational Databases
Proceedings of the VLDB Endowment, 9(12) (VLDB 2016), 2016.
DOI PDF Slides -
Visual Exploration of Machine Learning Results using Data Cube Analysis
Workshop on Human-In-the-Loop Data Analytics (HILDA at SIGMOD 2016), 2016.
Deployed by Facebook
DOI PDF Slides -
GLO-STIX: Graph-Level Operations for Specifying Techniques and Interactive eXploration
IEEE Transactions on Visualization and Computer Graphics, 20(12) (InfoVis 2014), 2014.
DOI PDF Video -
Exploiting Paths for Entity Search in RDF Graphs
ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2012) (Poster), 2012.
DOI PDF Poster -
Ranking Objects by Following Paths in Entity-Relationship Graphs
ACM Workshop for Ph.D. Students in Information and Knowledge Management (Ph.D. Workshop at CIKM 2011), 2011.
DOI PDF Slides -
Ranking in Context-Aware Recommender Systems
International Conference on World Wide Web (WWW 2011) (Poster), 2011.
DOI PDF Poster