Sublinear Time Force Computation for Big Complex Network Visualization. - Amyra Meidiana; Seok-Hee Hong 001; Marnijati Torkel; Shijun Cai; Peter Eades (Comput. Graph. Forum, 2020)

A Machine Learning Approach for Predicting Human Preference for Graph Layouts*. - Shijun Cai; Seok-Hee Hong 001; Jialiang Shen; Tongliang Liu (PacificVis, 2021)

Sublinear-Time Attraction Force Computation for Large Complex Graph Drawing. - Amyra Meidiana; Seok-Hee Hong 001; Shijun Cai; Marnijati Torkel; Peter Eades (PacificVis, 2021)

DNC: Dynamic Neighborhood Change Faithfulness Metrics. - Shijun Cai; Amyra Meidiana; Seok-Hee Hong 001 (EuroVis (Short Papers), 2022)

A Machine Learning Approach for Predicting Human Preference for Graph Layouts. - Shijun Cai; Seok-Hee Hong 001; Jialiang Shen; Tongliang Liu (J. Graph Algorithms Appl., 2022)

A machine learning approach for predicting human shortest path task performance. - Shijun Cai; Seok-Hee Hong 001; Xiaobo Xia; Tongliang Liu; Weidong Huang 001 (Vis. Informatics, 2022)

Cluster-Faithful Graph Visualization: New Metrics and Algorithms. - Shijun Cai; Seok-Hee Hong 001; Amyra Meidiana; Peter Eades; Daniel A. Keim (PacificVis, 2024)

SubLinearForce: Fully Sublinear-Time Force Computation for Large Complex Graph Drawing. - Amyra Meidiana; Seok-Hee Hong 001; Shijun Cai; Marnijati Torkel; Peter Eades (IEEE Trans. Vis. Comput. Graph., 2024)