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Rong Zhu
- Author ID
- u2028
- ORCID
-
-
- Links
-
(found by gpt-5.6-luna on jul 24 2026)
- Most Frequent Institution
- Alibaba
- Pagerank
- 0.11578511
- Overall Rank
- 558 | 97.43%
- Paper Count
- 13
Affiliation Timeline
-
Alibaba
Most frequent
2019 - 2026
| 13 papers
Incoming Non-self Citations Over Time
Total yearly non-self incoming citations across all papers by this author.
Publications by Paper Pagerank
Showing all 13 publications. Total citations include self and non-self citations.
| Rank |
Title |
Year |
Venue |
Total Citations |
Pagerank |
| 211 |
AliGraph: A Comprehensive Graph Neural Network Platform |
2019 |
VLDB |
63 |
0.00024805216 |
| 981 |
Cardinality Estimation in DBMS: A Comprehensive Benchmark Evaluation |
2022 |
VLDB |
80 |
0.00012713454 |
| 2,002 |
FLAT: Fast, Lightweight and Accurate Method for Cardinality Estimation |
2021 |
VLDB |
51 |
9.2076835e-05 |
| 2,209 |
Lero: A Learning-to-Rank Query Optimizer |
2023 |
VLDB |
41 |
8.8360101e-05 |
| 2,775 |
GraphScope: A Unified Engine For Big Graph Processing |
2021 |
VLDB |
30 |
8.0288982e-05 |
| 4,299 |
ALECE: An Attention-based Learned Cardinality Estimator for SPJ Queries on Dynamic Workloads |
2024 |
VLDB |
23 |
6.6766173e-05 |
| 4,366 |
DILI: A Distribution-Driven Learned Index |
2023 |
VLDB |
14 |
6.6330579e-05 |
| 5,438 |
Eraser: Eliminating Performance Regression on Learned Query Optimizer |
2024 |
VLDB |
11 |
6.1278045e-05 |
| 5,700 |
PilotScope: Steering Databases with Machine Learning Drivers |
2024 |
VLDB |
12 |
6.028998e-05 |
| 6,408 |
A Unified Transferable Model for ML-Enhanced DBMS |
2022 |
CIDR |
13 |
5.7921918e-05 |
| 10,149 |
BridgeScope: A Universal Toolkit for Bridging Large Language Models and Databases |
2026 |
CIDR |
1 |
5.0691578e-05 |
| 10,222 |
PRICE: A Pretrained Model for Cross-Database Cardinality Estimation |
2025 |
VLDB |
1 |
5.0560976e-05 |
| 11,033 |
Bridging LLMs and Database Systems: A Deep Dive into Enhanced Relational Operators |
2026 |
VLDB |
0 |
4.9769913e-05 |
Frequent Co-authors
Co-authored at least 5 papers.