| 2023 | SIGMOD | Demonstration of ThalamusDB: Answering Complex SQL Queries with Natural Language Predicates on Multi-Modal Data. | Saehan Jo, Immanuel Trummer |
| 2022 | SIGMOD | ISUM: Efficiently Compressing Large and Complex Workloads for Scalable Index Tuning. | Tarique Siddiqui, Saehan Jo, Wentao Wu, Chi Wang, Vivek R. Narasayya, Surajit Chaudhuri |
| 2020 | CIDR | BitGourmet: Deterministic Approximation via Optimized Bit Selection. | Saehan Jo, Immanuel Trummer |
| 2020 | SIGMOD | Demonstration of BitGourmet: Data Analysis via Deterministic Approximation. | Saehan Jo, Immanuel Trummer |
| 2019 | SIGMOD | Verifying Text Summaries of Relational Data Sets. | Saehan Jo, Immanuel Trummer, Weicheng Yu, Xuezhi Wang, Cong Yu, Daniel Liu, Niyati Mehta |
| 2019 | SIGMOD | SkinnerDB: Regret-Bounded Query Evaluation via Reinforcement Learning. | Immanuel Trummer, Junxiong Wang, Deepak Maram, Samuel Moseley, Saehan Jo, Joseph Antonakakis |
| 2018 | WSDM | Fast and Scalable Distributed Loopy Belief Propagation on Real-World Graphs. | Saehan Jo, Jaemin Yoo, U Kang |
| 2017 | ICDM | Supervised Belief Propagation: Scalable Supervised Inference on Attributed Networks. | Jaemin Yoo, Saehan Jo, U Kang |