Yu-Jung Ko
CS Ph.D candidate at Stony Brook Univeristy. Former Machine Learning Software Engineering Intern at Facebook. Touch-based Pointing Models, accessible computational design, reinforcement and deep learning.
yujko at cs (dot) stonybrook (dot) edu
Publication
- Yu-Jung Ko, Hang Zhao, Yoonsang Kim, IV Ramakrishnan, Shumin Zhai, and Xiaojun Bi. 2020. Modeling Two Dimensional Touch Pointing. In Proceedings of the 33rd Annual ACM Symposium on User Interface Software and Technology (UIST ‘20). Pages 858–868. DOI: https://doi.org/10.1145/3379337.3415871
- Syed Masum Billah, Yu-Jung Ko, Vikas Ashok, Xiaojun Bi, and IV Ramakrishnan. 2019. Accessible Gesture Typing for Non-Visual Text Entry on Smartphones. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (CHI ’19). Association for Computing Machinery, New York, NY, USA, Paper 376, 1–12. DOI:https://doi.org/10.1145/3290605.3300606
- Ryan Qin, Suwen Zhu, Yu-Hao Lin, Yu-Jung Ko, and Xiaojun Bi. 2018. Optimal-T9: An Optimized T9-like Keyboard for Small Touchscreen Devices. In Proceedings of the 2018 ACM International Conference on Interactive Surfaces and Spaces (ISS ’18). Association for Computing Machinery, New York, NY, USA, 137–146. DOI:https://doi.org/10.1145/3279778.3279786
- Yu-Hao Lin, Suwen Zhu, Yu-Jung Ko, Wenzhe Cui, and Xiaojun Bi. 2018. Why Is Gesture Typing Promising for Older Adults? Comparing Gesture and Tap Typing Behavior of Older with Young Adults. In Proceedings of the 20th International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS ’18). Association for Computing Machinery, New York, NY, USA, 271–281. DOI:https://doi.org/10.1145/3234695.3236350