My research focuses on advancing automation in real-world applications through program
synthesis and symbolic reasoning. My
primary
research directions are: 1) Developing core algorithms and necessary architectural support that
ensure scalable,
robust program synthesis methods, and 2) Applying these techniques to create practical,
user-friendly solutions
for real-world scenarios. Recently, I have been exploring how to leverage modern computational power
to enable
large-scale program synthesis.
Publications
(* equal contributions, Rui Dong is underlined.)
Presynthesis: Towards Scaling Up Program Synthesis with Finer-Grained Abstract Semantics Rui Dong, Qingyue Wu, Danny Ding, Zheng Guo, Ruyi Ji, Xinyu Wang.
PLDI, 2026.
Efficient Bottom-Up Synthesis for Programs with Local Variables
Xiang Li*, Xiangyu Zhou*, Rui Dong, Yihong Zhang, Xinyu Wang.
POPL, 2024.
[pdf] [artifact]
SlabCity: Whole-Query Optimization using Program Synthesis Rui Dong*, Jie Liu*, Yuxuan Zhu, Cong Yan, Barzan Mozafari, Xinyu Wang.
VLDB, 2023.
[pdf] [benchmarks] [slides] [talk] [poster]
MIWA: Mixed-Initiative Web Automation for Better User Control and Confidence
Weihao Chen, Xiaoyu Liu, Jiacheng Zhang, Ian Iong Lam, Zhicheng Huang, Rui Dong, Xinyu Wang, Tianyi Zhang.
UIST, 2023.
[pdf] [artifact]
DiLogics: Creating Web Automation Programs with Diverse Logics
Kevin Pu, Jim Yang, Angel Yuan, Minyi Ma, Rui Dong, Xinyu Wang, Yan Chen, Tovi Grossman.
UIST, 2023.
[pdf] [demo]
SemanticOn: Specifying Content-Based Semantic Conditions for Web Automation Programs
Kevin Pu, Rainey Fu, Rui Dong, Xinyu Wang, Yan Chen, Tovi Grossman.
UIST, 2022.
Best Paper Honorable Mention
[pdf] [preview] [demo]
WebRobot: Web Robotic Process Automation using Interactive Programming-by-Demonstration Rui Dong, Zhicheng Huang, Ian Iong Lam, Yan Chen, Xinyu Wang.
PLDI, 2022.
[pdf] [slides] [talk]