Demo Data from EDBT 2026 / reviewers in the wild / expert
Gurkirat Singh Bajwa
dblp:336/7866
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2022
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 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.
| Computer graphics and multimedia
1 paper |
Geometric modeling and processing · 100% | |
| Software engineering, system software, and programming languages
1 paper |
Programming languages and type systems · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Geometric modeling and processing › mesh processing
mesh adaptation |
0.6 | 1 | 2022 | Declarative Specification for Unstructured Mesh Editing Algorithms · ACM Trans. Graph. 2022 |
Geometric modeling and processing
mesh generation |
0.6 | 1 | 2022 | Declarative Specification for Unstructured Mesh Editing Algorithms · ACM Trans. Graph. 2022 |
Programming languages and type systems › program specification
declarative specification |
0.2 | 1 | 2022 | Declarative Specification for Unstructured Mesh Editing Algorithms · ACM Trans. Graph. 2022 |
Methods — techniques the papers use, named apart from their topics
invariant checking · 1.1shared-memory parallelization · 0.6shared memory parallelization · 0.6
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | Declarative Specification for Unstructured Mesh Editing AlgorithmsabstractWe introduce a novel approach to describe mesh generation, mesh adaptation, and geometric modeling algorithms relying on changing mesh connectivity using a high-level abstraction. The main motivation is to enable easy customization and development of these algorithms via a declarative specification consisting of a set of per-element invariants, operation scheduling, and attribute transfer for each editing operation. We demonstrate that widely used algorithms editing surfaces and volumes can be compactly expressed with our abstraction, and their implementation within our framework is simple, automatically parallelizable on shared-memory architectures, and with guaranteed satisfaction of the prescribed invariants. These algorithms are readable and easy to customize for specific use cases. We introduce a software library implementing this abstraction and providing automatic shared-memory parallelization. Zhongshi Jiang, Jiacheng Dai, Yunfan Zhou, Jérémie Dumas, Qingnan Zhou, Gurkirat Singh Bajwa, Denis Zorin, Daniele Panozzo, Teseo Schneider |
ACM Trans. Graph. | 7 |