Hannah Kim

CS PhD @ Georgia Tech 🐝
email | github | linkedin | cv

Hello! I'm a CS Ph.D. candidate at Georgia Tech working with Dr. Haesun Park and Dr. Alex Endert in the fields of text mining, machine learning, and visual analytics.

My research aims to help people explore and interact with large-scale data, focusing on improving interpretability, interactivity, and scalability, by designing and developing interactive systems that tightly integrate algorithm, visualization, and user interaction.

Education

Georgia Institute of Technology, Atlanta, GA, USA

Aug 2015 - Current

Ph.D. in Computer Science

Advisor: Haesun Park

Aug 2013 - May 2015

M.S. in Computer Science (Machine Learning, GPA 4/4.0)

Seoul National University, Seoul, Republic of Korea

Mar 2011 - Aug 2013

M.S. in Business Administration (Accounting)

Mar 2006 - Feb 2011

B.S. in Mathematics (Minor in Business Administration)

Publication

ArchiText: Interactive Hierarchical Topic Modeling

Hannah Kim, Barry L. Drake, Alex Endert, and Haesun Park

IEEE Transactions on Visualization and Computer Graphics (TVCG), 2020.

[pdf] [talk]

TopicSifter: Interactive Search Space Reduction through Targeted Topic Modeling

Hannah Kim, Dongjin Choi, Barry L. Drake, Alex Endert, and Haesun Park

IEEE Conference on Visual Analytics Science and Technology (VAST), 2019.

[pdf] [talk]

Understanding Actors and Evaluating Personae with Gaussian Embeddings

Hannah Kim, Denys Katerenchuk, Dan Billet, Jun Huan, Haesun Park, and Boyang Li

AAAI Conference on Artificial Intelligence (AAAI), 2019.

[pdf] [slide]

VisIRR: An Interactive Visual System for Information Retrieval and Recommendation for Large-scale Document Data

Jaegul Choo, Hannah Kim, Edward Clarkson, Zicheng Liu, Changhyun Lee, Fuxin Li, Hanseung Lee, Ramki Kannan, Chad Stolper, John Stasko, and Haesun Park

ACM Transactions on Knowledge Discovery from Data (TKDD), 2017.

[pdf] [video]

High-Recall Document Retrieval from Large-Scale Noisy Documents via Visual Analytics based on Targeted Topic Modeling

Hannah Kim, Jaegul Choo, Alex Endert, and Haesun Park

IEEE Conference on Visual Analytics Science and Technology (VAST-Poster), 2017.

[pdf] [poster]

PIVE: Per-Iteration Visualization Environment for Real-time Interactions with Dimension Reduction and Clustering

Hannah Kim, Jaegul Choo, Changhyun Lee, Hanseung Lee, Chandan K. Reddy, and Haesun Park

AAAI Conference on Artificial Intelligence (AAAI), 2017.

[pdf] [poster] [video]

AxiSketcher: Interactive Nonlinear Axis Mapping through Users' Drawing on Visualization

B.C. Kwon, Hannah Kim, Emily Wall, Jaegul Choo, Haesun Park, and Alex Endert

IEEE Transactions on Visualization and Computer Graphics (TVCG), 2016.

[pdf] [video] [talk]

Visualization by Demonstration: An Interaction Paradigm for Visual Data Exploration

Bahador Saket, Hannah Kim, Eli T. Brown, and Alex Endert

IEEE Transactions on Visualization and Computer Graphics (TVCG), 2015.

[pdf] [code]

InterAxis: Steering Scatterplot Axes via Observation-Level Interaction

Hannah Kim, Jaegul Choo, Haesun Park, and Alex Endert

IEEE Transactions on Visualization and Computer Graphics (TVCG), 2015.

[pdf] [slide] [video] [demo]

Simultaneous Discovery of Common and Discriminative Topics via Joint Nonnegative Matrix Factorization

Hannah Kim, Jaegul Choo, Jingu Kim, Chandan K. Reddy, and Haesun Park

ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2015

[pdf] [slide]

Doubly-Supervised Embedding Based on Label Information and Intrinsic Clusters for Visualization

Hannah Kim, Jaegul Choo, Chandan K. Reddy, and Haesun Park

Neurocomputing, Volume 150, Part B, Number 12, pages 570-582, 2015

[pdf]

PIVE: Per-Iteration Visualization Environment for Supporting Real-time Interactions with Computational Methods

Jaegul Choo, Changhyun Lee, Hannah Kim, Hanseung Lee, Barry L. Drake, and Haesun Park

IEEE Conference on Visual Analytics Science and Technology (VAST-Poster), 2014, Best Poster Award.

[pdf] [video]

VisIRR: Visual Analytics for Information Retrieval and Recommendation for Large-Scale Document Data

Jaegul Choo, Changhyun Lee, Hannah Kim, Hanseung Lee, Zhicheng Liu, Ramakrishnan Kannan, Charles D. Stolper, John Stasko, Barry L. Drake, and Haesun Park

IEEE Conference on Visual Analytics Science and Technology (VAST-Poster), 2014

[pdf] [video]

Exploring Anomalies in GAStech: VAST Mini Challenge 1 and 2

Jaegul Choo, Yi Han, Mengdie Hu, Hannah Kim, James Nugent, Francesco Poggi, Haesun Park, and John Stasko

IEEE Conference on Visual Analytics Science and Technology (VAST Challenge), 2014

[pdf] [slide]