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Meihao Liao
- Author ID
- 23022
- ORCID
-
0000-0002-5808-3131
- Links
-
(found by gpt-5.2 on feb 8th, 2026)
- Most Frequent Institution
- Beijing Institute of Technology
- Pagerank
- 0.089110847
- Overall Rank
- 770 | 96.32%
- Paper Count
- 13
Affiliation Timeline
Incoming Non-self Citations Over Time
Total yearly non-self incoming citations across all papers by this author.
Publications by Paper Pagerank
Showing 13 of 13 publications.
| Rank |
Title |
Year |
Venue |
Pagerank |
| 5,294 |
Maximal Defective Clique Enumeration |
2023 |
SIGMOD |
6.34833e-05 |
| 5,497 |
Fast Maximal Clique Enumeration on Uncertain Graphs: A Pivot-based Approach |
2022 |
SIGMOD |
6.2648243e-05 |
| 6,226 |
Hereditary Cohesive Subgraphs Enumeration on Bipartite Graphs: The Power of Pivot-based Approaches |
2023 |
SIGMOD |
6.0101131e-05 |
| 7,020 |
Efficient Personalized PageRank Computation: A Spanning Forests Sampling Based Approach |
2022 |
SIGMOD |
5.7819367e-05 |
| 9,260 |
Efficient Resistance Distance Computation: the Power of Landmark-based Approaches |
2023 |
SIGMOD |
5.3572577e-05 |
| 9,335 |
Efficient Personalized PageRank Computation: The Power of Variance-Reduced Monte Carlo Approaches |
2023 |
SIGMOD |
5.3449422e-05 |
| 9,626 |
Efficient Index Maintenance for Effective Resistance Computation on Evolving Graphs |
2025 |
SIGMOD |
5.3018378e-05 |
| 10,028 |
One Index for All: Towards Efficient Personalized PageRank Computation for Every Damping Factor |
2026 |
SIGMOD |
5.1725247e-05 |
| 10,075 |
Efficient Exact Resistance Distance Computation on Small-Treewidth Graphs: a Labelling Approach |
2026 |
SIGMOD |
5.1725247e-05 |
| 10,272 |
Theoretically and Practically Efficient Resistance Distance Computation on Large Graphs |
2026 |
VLDB |
5.1725247e-05 |
| 10,960 |
Efficient and Provable Effective Resistance Computation on Large Graphs: an Index-based Approach |
2024 |
SIGMOD |
5.1725247e-05 |
| 10,962 |
Efficient Maximal Biplex Enumerations with Improved Worst-Case Time Guarantee |
2024 |
SIGMOD |
5.1725247e-05 |
| 13,166 |
LightDiC: A Simple yet Effective Approach for Large-scale Digraph Representation Learning |
2024 |
VLDB |
- |
Frequent Co-authors
Co-authored at least 5 papers.