Hi, I'm a Research Scientist at Google in the People + AI Research (PAIR) team. I build novel visual analytics tools for people to responsibly develop and interactively interpret AI systems for large datasets. These interactive tools empower humans to discover insights about AI behavior using scalable data-driven techniques. This research contributes innovative methods and tools at the intersection of Data Visualization and Responsible AI.
Before joining Google, I was an Assistant Professor at Oregon State University, leading the Data Interaction and Visualization Lab. I received my Ph.D. in Computer Science from Georgia Tech with a Dissertation Award.
I currently live in the Atlanta area with my beloved partner Youjin Kong.
Featured Publications (Latest & Greatest)
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VLSlice: Interactive Vision-and-Language Slice Discovery
ICCV 2023
PDF Website -
Visualizing Linguistic Diversity of Text Datasets Synthesized by Large Language Models
VIS 2023 (Short)
PDF -
DendroMap: Visual Exploration of Large-Scale Image Datasets for Machine Learning with Treemaps
VIS 2022
DOI PDF Twitter Post Demo -
FitVid: Responsive and Flexible Video Content Adaptation
CHI 2022
DOI PDF -
Finding AI's Faults with AAR/AI: An Empirical Study
ACM Transactions on Interactive Intelligent Systems, 12(1), 2022.
DOI PDF -
One Explanation is Not Enough: Structured Attention Graphs for Image Classification
NeurIPS 2021
arXiv PDF -
Contrastive Identification of Covariate Shift in Image Data
VIS 2021 (Short)
DOI PDF -
"Why did my AI agent lose?": Visual Analytics for Scaling Up After-Action Review
VIS 2021 (Short)
DOI PDF -
CNN Explainer: Learning Convolutional Neural Networks with Interactive Visualization
VIS 2020
DOI PDF Demo Video -
FairVis: Visual Analytics for Discovering Intersectional Bias in Machine Learning
VIS 2019
DOI PDF Blog Code -
GAN Lab: Understanding Complex Deep Generative Models using Interactive Visual Experimentation
VIS 2018
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), 2018.
Cited more than 500 times
DOI PDF Website Medium -
ActiVis: Visual Exploration of Industry-Scale Deep Neural Network Models
VIS 2017
Deployed on Facebook's ML Platform
DOI PDF Video Slides Website -
Interactive Browsing and Navigation in Relational Databases
VLDB 2016
DOI PDF Slides
Employment
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Google, Atlanta, GA
Oct. 2022 - present
Research Scientist, People+AI Research (PAIR) Team -
Oregon State University, Corvallis, OR
2019-2022
Assistant Professor of Computer Science, School of Electrical Engineering and Computer Science -
Google, Cambridge, MA
Summer 2017
Software Engineering Intern, People+AI Research (PAIR) Team -
Facebook, Menlo Park, CA
Summer 2016
Research Intern, Applied ML Research Group -
Facebook, Menlo Park, CA
Summer 2015
Research Intern, Applied ML Research Group
Education
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Ph.D. in Computer Science,
Georgia Institute of Technology, Atlanta, GA
2013-2019
Thesis: Human-Centered AI through Scalable Visual Data Analytics
Committee: Polo Chau (Advisor), 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 (Advisor: Sang-goo Lee) - B.S. in Electrical and Computer Engineering, Seoul National University, South Korea 2005-2009
Awards
- 2021 College of Computing Dissertation Award, Georgia Tech 2021
- Finalist, Facebook Research Award 2021
- ACM Trans. Interactive Intelligent Systems (TiiS) 2018 Best Paper, Honorable Mention 2020
- Google PhD Fellowship, Google AI 2018-2019
- Graduate TA of the Year in School of Computer Science, Georgia Tech 2018
- NSF Graduate Research Fellowship, National Science Foundation 2014-2017
- Best Paper Award, PhD Workshop at CIKM 2011
- National Scholarship for Science and Engineering, Korea Student Aid Foundation 2005-2009
Teaching
- CS 499/549. Visual Analytics, Oregon State University 2022
- CS 565. Human-Computer Interaction, Oregon State University 2020-2022
- CS 539. Data Visualization for Machine Learning, Oregon State University 2020
Bio
Minsuk Kahng is a Research Scientist at Google in the People + AI Research (PAIR) team. His research focuses on building visual analytics tools for people to interpret and interact with machine learning systems for large datasets. He combines human-centered interactive methods and data-driven scalable techniques at the intersection of Data Visualization, Explainable AI, and Human-Computer Interaction (HCI). Kahng's research has led to deployed technologies (e.g., ActiVis for Facebook) and open-sourced tools (e.g., GAN Lab developed with Google). His research has been recognized by pretious awards, including Google PhD Fellowship and NSF Graduate Research Fellowship, and supported by NSF, DARPA, Google, Facebook, and others. Prior to Google, Kahng was an Assistant Professor of Computer Science at Oregon State University. He received his Ph.D. from Georgia Tech with a Dissertation Award and received his Master's and Bachelor's degrees from Seoul National University in South Korea.