VLDB 2026 Research / reviewers in the wild / expert
David Schrader
dblp:41/274
· DBLP profile ↗
3ranked-venue papers
0as first author
0since 2021 · last 1996
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Databases, data management, data science and information retrieval · 2Systems, architecture and hardware · 1
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.
| Computer graphics and multimedia
2 papers |
Multimedia systems and quality of experience · 87% Multimedia analysis and retrieval · 13% | |
| Computer architecture, parallel and distributed computing, and storage systems
2 papers |
Parallel and multicore computing · 100% |
Topics — the 3 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Parallel and multicore computing › parallel architecture
massively parallel architecture |
0.0 | 1 | 1996 | Prospector: A Content-Based Multimedia Server for Massively Parallel Architectures · SIGMOD Conference 1996 |
Parallel and multicore computing › parallel architecture
massively parallel processing |
0.0 | 1 | 1996 | A Content-Based Multimedia Server for Massively Parallel Architectures · SIGMOD Conference 1996 |
Multimedia analysis and retrieval › multimedia analysis
content analysis |
0.0 | 1 | 1996 | A Content-Based Multimedia Server for Massively Parallel Architectures · SIGMOD Conference 1996 |
Methods — techniques the papers use, named apart from their topics
user-defined functions · 0.1parallel content analysis · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1996 | Multimodal query support in database serversabstractThis paper introduces a novel approach to optimizing and monitoring database queries which involve operations on multiple data types in a parallel multimedia engine. Our approach uses dataflow graphs to represent the multimedia operations in a query. We have extended the Actors parallel programming model by designing an agent model for query execution that incorporates extensions for efficient data streaming, agent migration, and agent cloning. We incorporate algorithms for dynamic run-time workload control of both the number of queries in the system as well as the number of instances of agents executing multimedia operators. We describe an approach for capturing cost statistics for user-defined functions that is used by the system to estimate and schedule the execution of nested user-defined functions. William O'Connell, Grace Au, David Schrader |
ICCD | 3 |
| 1996 | Prospector: A Content-Based Multimedia Server for Massively Parallel ArchitecturesabstractThe Prospector Multimedia Object Manager prototype is a general-purpose content analysis multimedia server designed for massively parallel processor environments. Prospector defines and manipulates user defined functions which are invoked in parallel to analyze/manipulate the contents of multimedia objects. Several computationally intensive applications of this technology based on large persistent datasets include: fingerprint matching, signature verification, face recognition, and speech recognition/translation [OIS96]. S. Choo, William O'Connell, G. Linderman, K. Ganapathi, Alexandros Biliris, Euthimios Panagos, David Schrader |
SIGMOD Conference | 8 |
| 1996 | A Content-Based Multimedia Server for Massively Parallel ArchitecturesabstractThe Teradata Multimedia Object Manager is a general-purpose content analysis multimedia server designed for symmetric multiprocessing and massively parallel processing environments. The Multimedia Object Manager defines and manipulates user-defined functions (UDFs), which are invoked in parallel to analyze or manipulate the contents of multimedia objects. Several computationally intensive applications of this technology, which use large persistent datasets, include fingerprint matching, signature verification, face recognition, and speech recognition/translation. William O'Connell, Ion Tim Ieong, David Schrader, C. Watson, Grace Au, Alexandros Biliris, S. Choo, P. Colin, G. Linderman, Euthimios Panagos, T. Walters |
SIGMOD Conference | 3 |