Demo Data from EDBT 2026 / reviewers in the wild / expert
Ali Jamadi
dblp:331/1348
· DBLP profile ↗
3ranked-venue papers
0as first author
3since 2021 · last 2025
0000-0002-2092-1953ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 2 · 2 since 2021Artificial intelligence and machine learning · 1 · 1 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.
| Theoretical computer science
1 paper |
Distributed computing theory · 100% | |
| Software engineering, system software, and programming languages
1 paper |
Concurrent programming · 100% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Distributed computing theory › concurrent objects
concurrent data structures |
0.7 | 1 | 2023 | Efficient Bounded Timestamping from Standard Synchronization Primitives · PODC 2023 |
Distributed computing theory
shared memory |
0.7 | 1 | 2023 | Efficient Bounded Timestamping from Standard Synchronization Primitives · PODC 2023 |
Distributed computing theory
timestamping |
0.7 | 1 | 2023 | Efficient Bounded Timestamping from Standard Synchronization Primitives · PODC 2023 |
Concurrent programming › synchronization
synchronization primitives |
0.2 | 1 | 2023 | Efficient Bounded Timestamping from Standard Synchronization Primitives · PODC 2023 |
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Efficient bounded timestamping from standard synchronization primitives
Benyamin Bashari, Ali Jamadi, Philipp Woelfel |
Distributed Comput. | 2 |
| 2023 | Efficient Bounded Timestamping from Standard Synchronization PrimitivesabstractBounded timestamps [10, 20] allow a temporal ordering of events in executions of concurrent algorithms. They are a fundamental and well studied building block used in many shared memory algorithms. A concurrent timestamp system keeps track of m timestamps, which is usually greater or equal to the number of processes in the system, n. A process may, at any point, obtain a new timestamp, and later determine a total order of all process's most recent timestamps. Known timestamp algorithms do not scale well in the number of processes. Getting a new timestamp takes at least a linear number of steps, and a lower bound by Israeli and Li [20] implies that each timestamp needs to be represented by at least Ω(m) bits. Benyamin Bashari, Ali Jamadi, Philipp Woelfel |
PODC | 2 |
| 2022 | ISAIR: Deep inpainted semantic aware image representation for background subtraction
Mahdi Abolfazli Esfahani, Ali Jamadi, Messiah Abolfazli Esfahani |
Expert Syst. Appl. | 2 |