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 transaction processing and cloud-native databases, 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

2022

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 Paper Extended

2021

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 Paper Extended

2019

Unsupervised Functional Dependency Discovery for Data Preparation

Zhihan Guo, Theodoros Rekatsinas

ICLR Workshop Paper Extended Poster

All publications →