Demo Data from SIGIR 2026 / reviewers in the wild / expert
Ravi Anupindi
dblp:56/3721
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 1991
—ORCID · unresolved
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1Systems, 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 architecture, parallel and distributed computing, and storage systems
1 paper |
Performance modeling and evaluation · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Performance modeling and evaluation
queueing models |
0.0 | 1 | 1991 | Control of batch processing systems · ICRA 1991 |
Performance modeling and evaluation
semiconductor wafer fabrication |
0.0 | 1 | 1991 | Control of batch processing systems · ICRA 1991 |
Methods — techniques the papers use, named apart from their topics
optimization · 0.0average cost analysis · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1991 | Control of batch processing systemsabstractThe authors describe loading policies for a batch processing machine, i.e., a machine that can process more than one job at a time, when the arrival times of jobs at the machine are uncertain. The study is motivated by the structure of process flows and the predominance of batch processing systems in a semiconductor wafer fabrication facility. The authors consider a two-stage serial-batch system with the serial stage (e.g., photolithography) feeding the batch (e.g., furnace). Machines in the serial stage process one job at a time; further, these machines are subject to failure. The following control limit policy for loading the batch machine is assumed: load if the queue length >or=Q, else wait until the number of jobs in queue is at least Q. The basic tradeoff considered is delayed vs. capacity utilization. The authors do an average cost analysis and optimize to compute the critical number Q.> Haresh Gurnani, Ravi Anupindi, Ram Akella |
ICRA | 2 |