What is he best known for?
The fields of study he is best known for:
- Operating system
- Programming language
- Database
Thomas Neumann mainly investigates Database, Query optimization, Information retrieval, Scalability and RDF.
His Database study frequently draws parallels with other fields, such as Multi-core processor.
His work carried out in the field of Query optimization brings together such families of science as Query language, Cardinality, Dynamic programming and Cardinality.
The study incorporates disciplines such as Ranking and World Wide Web in addition to Information retrieval.
In the subject of general RDF, his work in SPARQL is often linked to RDF query language, thereby combining diverse domains of study.
As a member of one scientific family, he mostly works in the field of SPARQL, focusing on Search engine indexing and, on occasion, Cwm and Joins.
His most cited work include:
- The RDF-3X engine for scalable management of RDF data (488 citations)
- HyPer: A hybrid OLTP&OLAP main memory database system based on virtual memory snapshots (475 citations)
- RDF-3X: a RISC-style engine for RDF (473 citations)
What are the main themes of his work throughout his whole career to date?
Thomas Neumann mainly focuses on Database, Query optimization, Theoretical computer science, Data mining and Distributed computing.
Online analytical processing, Online transaction processing, Database transaction, Snapshot and Scalability are the core of his Database study.
His Query optimization study combines topics from a wide range of disciplines, such as Query language, Query expansion and Cardinality.
His studies examine the connections between Theoretical computer science and genetics, as well as such issues in Joins, with regards to Hash function.
His studies deal with areas such as Workload, Server and Parallel computing as well as Distributed computing.
His RDF research is multidisciplinary, incorporating elements of Linked data and Search engine indexing.
He most often published in these fields:
- Database (23.81%)
- Query optimization (13.42%)
- Theoretical computer science (13.42%)
What were the highlights of his more recent work (between 2018-2021)?
- Scalability (9.52%)
- Artificial intelligence (3.90%)
- Programming language (4.33%)
In recent papers he was focusing on the following fields of study:
His primary scientific interests are in Scalability, Artificial intelligence, Programming language, SQL and Distributed computing.
His study on Scalability also encompasses disciplines like
- Overhead which intersects with area such as Key, Query optimization, Sampling, Precomputation and Random access,
- Synchronization that connect with fields like Record locking and Factor.
His SQL study is related to the wider topic of Database.
Thomas Neumann integrates Database with Direct memory access in his study.
The Distributed computing study combines topics in areas such as Volume, Database transaction, Analytics and Data stream mining.
His work carried out in the field of Information retrieval brings together such families of science as Raw data, Online analytical processing and Speedup.
Between 2018 and 2021, his most popular works were:
- Persistent Memory I/O Primitives (33 citations)
- The Seattle Report on Database Research (20 citations)
- SOSD: A Benchmark for Learned Indexes (14 citations)
In his most recent research, the most cited papers focused on:
- Operating system
- Programming language
- Database
His scientific interests lie mostly in Artificial intelligence, Machine learning, Benchmark, Index and Distributed computing.
His Distributed computing research incorporates themes from Scalability, Database transaction, Concurrency control, Isolation and Analytics.
His Scalability study combines topics from a wide range of disciplines, such as Synchronization, Record locking and Multiversion concurrency control.
He brings together Database transaction and Throughput to produce work in his papers.
His Concurrency control study incorporates themes from Serializability, Correctness, Online transaction processing and Garbage, Garbage collection.
His research integrates issues of Overhead, Transaction processing, Concurrency, Commit and Server in his study of Isolation.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
