About — Zhihan Guo

My interests lie at the intersection of database systems, distributed systems, and AI-native infrastructure. I am especially drawn to applications in healthcare, where I ultimately hope to see this infrastructure make a meaningful difference.

Education

Ph.D. in Computer Sciences, University of Wisconsin–Madison
Microsoft Research PhD Fellowship2021–22 · US & Canada

2019 - 2023 Advised by Prof. Xiangyao Yu.

Focused on scalable transaction processing in cloud-native OLTP database systems, leading to publications at SIGMOD, VLDB, and FAST.

2018 - 2019 Advised by Prof. Theodoros Rekatsinas

Focused on ML-driven data integration and data cleaning.
B.S. in Computer Sciences, University of Wisconsin–Madison

Selected Publications

Nemo: Efficient Caching with Index Pushdown for Disaggregated OLTP Databases

Wenjie Hu, Xinjing Zhou, Zhihan Guo, Xiangpeng Hao, Xiangyao Yu

SIGMOD 2027 To appear

Cornus: Atomic Commit for Cloud DBMS with Storage Disaggregation

Zhihan Guo, Xinyu Zeng, Kan Wu, Wuh-Chwen Hwang, Ziwei Ren, Xiangyao Yu, Mahesh Balakrishnan, Philip A. Bernstein

VLDB 2022 Paper Extended

Releasing Locks As Early As You Can: Reducing Contention of Hotspots by Violating Two-Phase Locking

Zhihan Guo, Kan Wu, Cong Yan, Xiangyao Yu

SIGMOD 2021 Paper Extended

Unsupervised Functional Dependency Discovery for Data Preparation

Zhihan Guo, Theodoros Rekatsinas

ICLR Workshop 2019 Paper Extended Poster

All publications →