| Sublinear time force computation for big complex network visualization A Meidiana, SH Hong, M Torkel, S Cai, P Eades Computer Graphics Forum 39 (3), 579-591, 2020 | 8 | 2020 |
| Sublinear-time attraction force computation for large complex graph drawing A Meidiana, SH Hong, S Cai, M Torkel, P Eades 2021 IEEE 14th Pacific Visualization Symposium (PacificVis), 146-150, 2021 | 3 | 2021 |
| A Machine Learning Approach for Predicting Human Preference for Graph Layouts* S Cai, SH Hong, J Shen, T Liu 2021 IEEE 14th Pacific Visualization Symposium (PacificVis), 6-10, 2021 | 2 | 2021 |
| A machine learning approach for predicting human shortest path task performance S Cai, SH Hong, X Xia, T Liu, W Huang Visual Informatics 6 (2), 50-61, 2022 | 1 | 2022 |
| SubLinearForce: Fully Sublinear-Time Force Computation for Large Complex Graph Drawing A Meidiana, SH Hong, S Cai, M Torkel, P Eades IEEE Transactions on Visualization and Computer Graphics, 2023 | | 2023 |
| DNC: Dynamic Neighborhood Change Faithfulness Metrics. S Cai, A Meidiana, SH Hong EuroVis (Short Papers), 49-53, 2022 | | 2022 |
| A Machine Learning Approach for Predicting Human Preference for Graph Drawings S Cai, SH Hong, J Shen, T Liu | | |
Seok-Hee HongProfessor of Computer Science, University of SydneyVerified email at sydney.edu.au
