TurboFlux: A Fast Continuous Subgraph Matching System for Streaming Graph Data. - Kyoungmin Kim 002; In Seo; Wook-Shin Han; Jeong-Hoon Lee 004; Sungpack Hong; Hassan Chafi; Hyungyu Shin; Geonhwa Jeong (SIGMOD Conference, 2018)

G-CARE: A Framework for Performance Benchmarking of Cardinality Estimation Techniques for Subgraph Matching. - Yeonsu Park; Seongyun Ko; Sourav S. Bhowmick; Kyoungmin Kim 002; Kijae Hong; Wook-Shin Han (SIGMOD Conference, 2020)

Combining Sampling and Synopses with Worst-Case Optimal Runtime and Quality Guarantees for Graph Pattern Cardinality Estimation. - Kyoungmin Kim 002; Hyeonji Kim; George Fletcher 001; Wook-Shin Han (SIGMOD Conference, 2021)

[Technical Report] Combining Sampling and Synopses with Worst-Case Optimal Runtime and Quality Guarantees for Graph Pattern Cardinality Estimation. - Kyoungmin Kim 002; Hyeonji Kim; George Fletcher 001; Wook-Shin Han (CoRR, 2021)

Learned Cardinality Estimation: An In-depth Study. - Kyoungmin Kim 002; Jisung Jung; In Seo; Wook-Shin Han; Kangwoo Choi; Jaehyok Chong (SIGMOD Conference, 2022)

Guaranteeing the Õ(AGM/OUT) Runtime for Uniform Sampling and Size Estimation over Joins. - Kyoungmin Kim 002; Jaehyun Ha; George Fletcher 001; Wook-Shin Han (PODS, 2023)

Guaranteeing the Õ(AGM/OUT) Runtime for Uniform Sampling and OUT Size Estimation over Joins. - Kyoungmin Kim 002; Jaehyun Ha; George Fletcher 001; Wook-Shin Han (CoRR, 2023)

ASM in Action: Fast and Practical Learned Cardinality Estimation. - Sangoh Lee; Kyoungmin Kim 002; Wook-Shin Han (SIGMOD Conference Companion, 2024)

The Effect of Scheduling and Preemption on the Efficiency of LLM Inference Serving. - Kyoungmin Kim 002; Kijae Hong; Caglar Gulcehre; Anastasia Ailamaki (CoRR, 2024)

Trustworthy and Efficient LLMs Meet Databases. - Kyoungmin Kim 002; Anastasia Ailamaki (CoRR, 2024)

In-depth Analysis of Continuous Subgraph Matching in a Common Delta Query Compilation Framework. - Yukyoung Lee; Kyoungmin Kim 002; Wonseok Lee; Wook-Shin Han (Proc. ACM Manag. Data, 2024)

ASM: Harmonizing Autoregressive Model, Sampling, and Multi-dimensional Statistics Merging for Cardinality Estimation. - Kyoungmin Kim 002; Sangoh Lee; Injung Kim 001; Wook-Shin Han (Proc. ACM Manag. Data, 2024)

Themis: A GPU-accelerated Relational Query Execution Engine. - Kijae Hong; Kyoungmin Kim 002; Young-Koo Lee; Yang-Sae Moon; Sourav S. Bhowmick; Wook-Shin Han (Proc. VLDB Endow., 2024)