Resume
Resume
Sep. 2019 - Sep. 2025
University of California, Riverside, United States
Ph.D. Computer Science
Advisor: Dr. Ahmed Eldawy
Research interest: big data management, approximate query processing, geospatial query processing
Jan. 2017 - Dec. 2018
Washington State University, United States
M.S. Computer Science
Advisor: Dr. Yinghui Wu
Research interest: Graph Database and keyword search
Sep. 2012 - Jun. 2016
Shandong University, China
B.S. Software Engineering
Aug. 2025 - current
SDE, Amazon AWS Redshift, Query Optimzier Team
Sep. 2025 - Jun. 2020
Research Assistant, University of California, Riverside Advisor: Dr. Ahmed Eldawy
We are working on building a Data Lakehouse system for incrementally combining data synopses. This system use the data synopses to help users to perform approximate OLAP queries over Data Lake. This work is under submission.
Worked on building a quality-aware progressive join framework, which can progressive process equi-join and spatial join. Based on the framework, we build a system that can handle relational and spatial data and visualize the query results.
Jun.2024 - Aug.2024
SDE Summer Intern, Amazon AWS Redshift Mentor: Martin Milenkoski, Manager: Mohammed Alkateb
Jun. 2021 - Aug. 2021
Research Summer Intern, IBM Research, Almaden Mentor: Ronald Barber, Richard Sidle
Worked on building LSM-tree based database.
Sep. 2019 - Jun. 2021
Research Assistant, University of California, Riverside Advisor: Dr. Vagelis Hristidis
Worked on optimizing LSM-tree based database. We are trying to come up with a new merge policy for improving the read performance of the LSM-tree based database.
Jan. 2017 - Dec. 2018
Research Assistant, Washington State University
Advisor: Dr. Yinghui Wu
Worked on designing Kronos system. The system aims to automatically extract highly dynamic knowledge for complex event analysis in Cyber-Physical systems. I worked on building a dynamic knowledge base, and incremental association analysis for event detection and linkage.
Worked on graph exploration projects and published two papers and one patent related to this topic. We developed a system called GExp. GExp interleaves keyword query suggestion, which generates keyword queries that expand the original query and query evaluation, which returns the answers to suggested queries for feedback. Totally, there are three baseline algorithms to find the initial query results, I worked on implementing one of them. Also, I worked on building the evaluation matrices of query suggestions.
SIGMOD Student Research Competition, Second Place, 2023
Studend Travel Award, SIGMOD 2023, ICDE 2023
Dean’s Distinguished Fellowship, UC Riverside, 2019
The First-class Award of Outstanding Student in the Summer School of Visual Computing, Shandong University, 2015
The Third-class Scholarship, Shandong University, 2014, 2015