Hi, I'm an Assistant Professor of Computer Science in the School of Electrical Engineering and Computer Science at Oregon State University.
The goal of my research is to make AI more accessible and interpretable, or broadly human-centered. Specifically, my research focuses on building novel interactive, visual analytics tools for people to easily explore, interpret, and interact with ML systems and large datasets. To do this, my work combines data-driven scalable techniques and human-centered interactive approaches, by utilizing methods from multiple areas, including data visualization, interpretable machine learning, databases, and HCI.
I received a PhD in computer science at Georgia Tech, advised by Polo Chau. During my PhD studies, I was fortunate to work with amazing people at Google Brain and Facebook Research, resulting in publications, deployed systems by Facebook (e.g., on visualization of deep learning models), and open-sourced tools developed with Google Brain (e.g., on deep learning education).
I have been supported by a Google PhD Fellowship and an NSF Graduate Research Fellowship. Prior to Georgia Tech, I completed both my master's and bachelor's degrees at Seoul National University in South Korea.
I'm looking for current OSU students interested in human-centered AI, data visualization, or more. Email me if you're interested.
News
- Oct 2019 Presented on the evaluation of GAN Lab at EVIVA-ML Workshop at VIS.
- Oct 2019 I successfully defended my dissertation.
- July 2019 New paper, FairVis, on visual analysis of ML bias accepted to IEEE VIS'19.
- June 2019 I'll be joining Oregon State University as an Assistant Professor this winter!
- Sept 2018 New paper, GAN Lab, accepted to IEEE VIS'18. Try our live system here!
Research Highlights
Education
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Ph.D. 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
- National Scholarship for Science and Engineering, Korea Student Aid Foundation 2005-2009
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: 14)
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FairVis: Visual Analytics for Discovering Intersectional Bias in Machine Learning
IEEE Conference on Visual Analytics Science and Technology (VAST'19), 2019.
arXiv PDF Blog Code -
How Does Visualization Help People Learn Deep Learning? Evaluation of GAN Lab
Workshop on Evaluation of Interactive Visual Machine Learning Systems (EVIVA-ML at IEEE VIS'19), 2019.
PDF -
GAN Lab: Understanding Complex Deep Generative Models using Interactive Visual Experimentation
IEEE Transactions on Visualization and Computer Graphics, 25(1) (VAST'18), 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, 25(8), 2019.
DOI PDF Website Medium -
ActiVis: Visual Exploration of Industry-Scale Deep Neural Network Models
IEEE Transactions on Visualization and Computer Graphics, 24(1) (VAST'17), 2018.
Deployed on Facebook ML Platform; Invited to present at SIGGRAPH'18 as a top VIS paper (4 total)
DOI PDF Video Slides Website -
FACETS: Adaptive Local Exploration of Large Graphs
SIAM International Conference on Data Mining (SDM'17), 2017.
DOI PDF -
mHealth Visual Discovery Dashboard
ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp'17) (Demo), 2017.
PDF Video -
Interactive Browsing and Navigation in Relational Databases
Proceedings of the VLDB Endowment, 9(12) (VLDB'16), 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'16), 2016.
Deployed on Facebook ML Platform
DOI PDF Slides -
GLO-STIX: Graph-Level Operations for Specifying Techniques and Interactive eXploration
IEEE Transactions on Visualization and Computer Graphics, 20(12) (InfoVis'14), 2014.
DOI PDF Video -
Exploiting Paths for Entity Search in RDF Graphs
ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'12) (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'11), 2011.
Best Paper Award
DOI PDF Slides -
Ranking in Context-Aware Recommender Systems
International Conference on World Wide Web (WWW'11) (Poster), 2011.
DOI PDF Poster