Hi, I'm a Research Scientist at Google in the People + AI Research (PAIR) team, part of the Responsible AI group.
My research aims to empower researchers and practitioners to gain insights from interactive data visualization, enabling them to responsibly develop AI systems. To achieve this goal, I build novel visual analytics tools that help these people explore large datasets for AI.
At Google, I develop interactive data visualization tools for the development of large language models (LLMs). These tools have been successfully deployed in Google engineers' workflows to interpret the behavior of LLMs, discover bias and errors, and improve their datasets.
Before joining Google, I was an Assistant Professor at Oregon State University. I received my Ph.D. from Georgia Tech, advised by Polo Chau, and was recognized by an NSF Graduate Research Fellowship, a Google PhD Fellowship, and a Georgia Tech Dissertation Award.
Areas of expertise: Data Visualization, Visual Analytics, Responsible AI, Explainable AI, Human-Computer Interaction
Selected Publications (Latest & Greatest)
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LLM Comparator: Visual Analytics for Side-by-Side Evaluation of Large Language Models
CHI 2024 (LBW track) (To appear)
arXiv PDF
Deployed on Google's LLM Evaluation Platforms -
Automatic Histograms: Leveraging Language Models for Text Dataset Exploration
CHI 2024 (LBW track) (To appear)
arXiv PDF -
Understanding the Dataset Practitioners Behind Large Language Model Development
CHI 2024 (LBW track) (To appear)
arXiv PDF -
Adversarial Nibbler: An Open Red-Teaming Method for Identifying Diverse Harms in Text-to-Image Generation
FAccT 2024 (To appear)
arXiv PDF -
VLSlice: Interactive Vision-and-Language Slice Discovery
ICCV 2023
arXiv PDF Talk Website -
Visualizing Linguistic Diversity of Text Datasets Synthesized by Large Language Models
VIS 2023 (Short)
PDF Code -
DendroMap: Visual Exploration of Large-Scale Image Datasets for Machine Learning with Treemaps
VIS 2022
DOI arXiv PDF Twitter Post Demo -
FitVid: Responsive and Flexible Video Content Adaptation
CHI 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 600 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
2022 - present
Senior Research Scientist, People+AI Research (PAIR) Team, Responsible AI and Human-Centered Technology -
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, Google Brain -
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, and 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
- 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
Professional Service
- Conf. Organization VIS 2024 (Publication Chairs), IDEA@KDD 2018 (Workshop Organiziers), WSDM 2016 (Web)
- Conf. PC VIS (2020-present), IUI (2019-present), AAAI (2021-22), SDM (2020), WSDM (2022 Demo), CIKM (2019 Demo)
- Journal Reviewers IEEE TVCG, ACM TiiS, ACM TOCHI, ACM TIST, Distill
- Conf. Reviewers CHI (2014, 17-18, 21-22, 24), UIST (2023), CSCW (2020), VIS (2018-20), EuroVis (2018), KDD (2014-16), SDM (2014, 16-17), IUI (2016), RecSys (2016), SIGMOD (2013), DASFAA (2011)
- Grant Reviewers NSF Review Panelists (CISE III)
Bio
Minsuk Kahng is a Senior Research Scientist at Google in the People + AI Research (PAIR) team.
His research aims to empower researchers and practitioners to gain insights from interactive data visualization,
enabling them to responsibly develop AI systems.
To achieve this goal, he builds novel visual analytics tools that help these people
interpret model behavior and explore large datasets.
Kahng publishes papers at the top venue in the field of data visualization (IEEE VIS),
as well as at premier conferences in the field of AI, Human-Computer Interaction,
Data Science, and Responsible Computing.
His research has led to deployed technologies (e.g., LLM Comparator for Google, ActiVis for Facebook)
and open-sourced tools (e.g., GAN Lab, FairVis), and
his work has been recognized by prestigious awards, including
Google PhD Fellowship and NSF Graduate Research Fellowship, and
supported by NSF, DARPA, Google, and NAVER.
Prior to Google, he was an Assistant Professor 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.
Website: https://minsuk.com
CV: https://minsuk.com/minsuk-kahng-cv.pdf