VLDB 2026 Research / reviewers in the wild / expert
Amrish Kumar
dblp:154/5841
· DBLP profile ↗
2ranked-venue papers
0as first author
2since 2021 · last 2023
—ORCID · unresolved
Domains — the database's venue-derived domains; a paper can count in several
Databases, data management, data science and information retrieval · 1 · 1 since 2021Graphics, 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 architecture, parallel and distributed computing, and storage systems
1 paper |
Cloud and datacenter computing · 56% High-performance computing · 44% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Cloud and datacenter computing
big data platform |
0.5 | 1 | 2021 | The Cosmos Big Data Platform at Microsoft: Over a Decade of Progress and a Decade to Look Forward · Proc. VLDB Endow. 2021 |
High-performance computing › data-intensive computing
large-scale data processing |
0.5 | 1 | 2021 | The Cosmos Big Data Platform at Microsoft: Over a Decade of Progress and a Decade to Look Forward · Proc. VLDB Endow. 2021 |
Methods — techniques the papers use, named apart from their topics
distributed systems design · 0.5
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2023 | Performance evaluation of ANFIS, ANN and RSM in biodiesel synthesis from Karanja oil with Domestic Microwave set up
Jasbir Singh, Vivudh Fore, Amrish Kumar |
Multim. Tools Appl. | 4 |
| 2021 | The Cosmos Big Data Platform at Microsoft: Over a Decade of Progress and a Decade to Look ForwardabstractThe twenty-first century has been dominated by the need for large scale data processing, marking the birth of big data platforms such as Cosmos. This paper describes the evolution of the exabyte-scale Cosmos big data platform at Microsoft; our journey right from scale and reliability all the way to efficiency and usability, and our next steps towards improving security, compliance, and support for heterogeneous analytics scenarios. We discuss how the evolution of Cosmos parallels the evolution of the big data field, and how the changes in the Cosmos workloads over time parallel the changing requirements of users across industry. Conor Power, Hiren Patel, Alekh Jindal, Jyoti Leeka, Bob Jenkins, Michael Rys, Ed Triou, Dexin Zhu, Lucky Katahanas, Chakrapani Bhat Talapady, Josh Rowe, Rich Draves, Ivan Santa, Amrish Kumar |
Proc. VLDB Endow. | 15 |