Demo Data from VLDB 2026 / reviewers in the wild / expert
Mingwei Samuel
dblp:266/6089
· DBLP profile ↗
2ranked-venue papers
1as first author
1since 2021 · last 2026
0009-0004-9873-6266ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 1 · 1 since 2021Databases, data management, data science and information retrieval · 1 · 1 first-author
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 |
Indexing and storage engines · 50% Query processing and optimization · 50% |
Topics — the 1 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Indexing and storage engines › in-memory storage
in-memory data layout |
0.4 | 1 | 2020 | Demonstration of Chestnut: An In-memory Data Layout Designer for Database Applications · SIGMOD Conference 2020 |
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | Stageleft: Multi-stage Programming in Standard Rust
Shadaj Laddad, Mingwei Samuel, Joseph M. Hellerstein |
GPCE | 2 |
| 2020 | Demonstration of Chestnut: An In-memory Data Layout Designer for Database ApplicationsabstractThis demonstration showcases Chestnut, a data layout generator for in-memory object-oriented database applications. Given an application and a memory budget, Chestnut generates a customized in-memory data layout and the corresponding query plans that are specialized for the application queries. Our demo will let users design and improve simple web applications using Chestnut. Users can view the Chestnut-generated data layouts using a custom visualization system, which will allow users to see how the application parameters affect Chestnut's design. Finally, users will be able to run queries generated by the application via the customized query plans generated by Chestnut or traditional relational query engines, and can compare the results and observe the speedup achieved by the Chestnut-generated query plans. Mingwei Samuel, Cong Yan, Alvin Cheung |
SIGMOD Conference | 1 |