Scholar
Kexin Rong
Google Scholar ID: C8LDYK0AAAAJ
School of Computer Science, Georgia Institute of Technology
Data
Data Management
Data Systems
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Homepage
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Google Scholar
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Citations & Impact
All-time
Citations
360
H-index
10
i10-index
11
Publications
20
Co-authors
7
list available
Contact
Email
krong@gatech.edu
CV
Open ↗
GitHub
Open ↗
Publications
4 items
Halo: Domain-Aware Query Optimization for Long-Context Question Answering
2026
Cited
0
ActionEngine: From Reactive to Programmatic GUI Agents via State Machine Memory
2026
Cited
0
HoneyBee: Efficient Role-based Access Control for Vector Databases via Dynamic Partitioning
2025
Cited
0
A Socratic RAG Approach to Connect Natural Language Queries on Research Topics with Knowledge Organization Systems
2025
Cited
0
Resume (English only)
Academic Achievements
[June 2025] Student Peng Li won the SIGMOD 2025 Jim Gray Doctoral Dissertation Award
[June 2024] Received SIGMOD 2024 Distinguished PC Award
[Apr 2024] Awarded Amazon Research Award for optimizing layout designs in data analytics systems
[Apr 2024] Received NSF award to reimagine video retrieval with hand-drawn sketches
[Oct 2023] Received NSF award to build a person-focused open knowledge graph
[Oct 2023] Student Hantian Zhang won the Chih Foundation Graduate Student Research Publication Award
[Aug 2023] Student Peng Li won Best Research Paper Award at VLDB'23
[Aug 2023] Recognized as Distinguished Reviewer for PVLDB Vol.16
[Jun 2022] Honorable Mention for SIGMOD Jim Gray Doctoral Dissertation Award
[Aug 2022] Awarded Catherine M. and James E. Allchin Early Career Professorship
Published papers at top venues including SIGMOD, VLDB, ICDE, SoCC
Work adopted by industry (e.g., Datadog, TimescaleDB)
Background
Assistant Professor in the School of Computer Science at Georgia Tech
Research focuses on systems and algorithms to improve computational and human efficiency in large-scale data analytics
Member of the Georgia Tech database group
Affiliated researcher at VMware Research Group
Broadly interested in democratizing data science by building systems and tools that make data analysis more efficient and accessible to non-experts
Co-authors
7 total
Peter Bailis
Workday
Philip Levis
Professor of Computer Science, Stanford University
Moses Charikar
Professor of Computer Science, Stanford University
Co-author 4
Joy Arulraj
Georgia Institute of Technology
Srikanth Kandula
Amazon Web Services
Steven Euijong Whang
Associate Professor with Tenure at KAIST EE and AI
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