VLDB 2026 Research / reviewers in the wild / expert
Nils L. Schubert
dblp:349/0770
· DBLP profile ↗
3ranked-venue papers
2as first author
3since 2021 · last 2026
0009-0001-0909-2082ORCID · verified
Domains — the database's venue-derived domains; a paper can count in several
Databases, data management, data science and information retrieval · 3 · 2 first-author · 3 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Databases, data mining, and information retrieval
1 paper |
Data stream processing · 100% | |
| Computer networks
1 paper |
Edge and fog computing · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Data stream processing
stream processing systems |
0.9 | 1 | 2025 | Incremental Stream Query Deployment under Continuous Infrastructure Changes in the Cloud-Edge Continuum · Proc. VLDB Endow. 2025 |
Edge and fog computing
cloud-edge continuum |
0.9 | 1 | 2025 | Incremental Stream Query Deployment under Continuous Infrastructure Changes in the Cloud-Edge Continuum · Proc. VLDB Endow. 2025 |
Methods — techniques the papers use, named apart from their topics
incremental deployment · 1.7
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | NebulaStream: An Adaptive and Efficient Multi-Query Stream Processing Engine
Nils L. Schubert, Lukas Schwerdtfeger, Sara Schnaterbeck, Philipp M. Grulich, Bonaventura Del Monte, Steffen Zeuch, Volker Markl |
ICDE | 1 |
| 2025 | Incremental Stream Query Deployment under Continuous Infrastructure Changes in the Cloud-Edge Continuum
Ankit Chaudhary 0002, Felix Lang, Danila Ferents, Nils L. Schubert, Varun Pandey, Jeyhun Karimov, Steffen Zeuch, Kaustubh Beedkar, Volker Markl |
Proc. VLDB Endow. | 4 |
| 2023 | Exploiting Access Pattern Characteristics for Join ReorderingabstractWith increasing main memory sizes, data processing has significantly shifted from secondary storage to main memory. However, choosing a good join order is still very important for efficient query execution in modern DBMS. This choice bases mainly on cardinality estimates for intermediate join results. However, the memory access pattern, e.g., sequential or random, on the intermediate state is an often neglected performance factor. Nils L. Schubert, Philipp M. Grulich, Steffen Zeuch, Volker Markl |
DaMoN | 1 |