Immanuel Trummer

1.1k citations
65 papers · 603 indexed · h-index 16

Impact in

    • Data Management and Algorithms
    • Topic Modeling
    • Quantum Computing Algorithms and Architecture
    • Data Stream Mining Techniques
    • Semantic Web and Ontologies

Papers in

Immanuel Trummer

52 papers receiving 583 citations

Peers

Immanuel Trummer
Comparison fields: 5 of 62
  • Signal Processing 127
  • Artificial Intelligence 354
  • Computer Networks and Communications 250
  • Information Systems 203
  • Computer Science Applications 40
Replace Marina Drosou with:
Marina Drosou Greece
Manas Joglekar United States
Jaroslaw Szlichta Canada
Hazem Elmeleegy United States
Bhargav Kanagal United States
Stephan Seufert Germany
Olga Ohrimenko Australia
Kenji Hatano Japan
Ullas Nambiar United States
Byron J. Gao United States
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Citations per field
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Citations per year

Countries citing papers authored by Immanuel Trummer

Since Specialization
Citations

This map shows the geographic impact of Immanuel Trummer's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Immanuel Trummer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Immanuel Trummer more than expected).

Fields of papers citing papers by Immanuel Trummer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Immanuel Trummer. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Immanuel Trummer. The network helps show where Immanuel Trummer may publish in the future.

Co-authors

The 25 scholars most cited alongside Immanuel Trummer, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Immanuel Trummer Line = papers co-authored together Immanuel Trummer links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 65 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201645
2 202241
3 201336
4 202235
5 201433
6 202127
7 202327
8 202125
9 201723
10 201822
11 202021
12 201420
13 201419
14 202218
15 201015
16 202115
17 201915
18 201515
19 201911
20 202310

About Immanuel Trummer

Immanuel Trummer is a scholar working on Signal Processing, Computer Networks and Communications, Artificial Intelligence, Information Systems and Management Science and Operations Research, having authored 65 papers that have together received 603 indexed citations. Recurring topics across this work include Advanced Database Systems and Queries (29 papers), Data Management and Algorithms (22 papers), Semantic Web and Ontologies (11 papers), Topic Modeling (11 papers), Constraint Satisfaction and Optimization (10 papers), Natural Language Processing Techniques (8 papers), Data Quality and Management (8 papers) and Data Stream Mining Techniques (7 papers). The work is most often cited by research in Signal Processing (127 citations), Artificial Intelligence (354 citations), Computer Networks and Communications (250 citations), Information Systems (203 citations) and Computer Science Applications (40 citations). Immanuel Trummer has collaborated with scholars based in United States, Switzerland and France. Frequent co-authors include Christoph Koch, Walter Binder, Junxiong Wang, Boi Faltings, Georgios Karagiannis, Thanasis G. Papaioannou, Mehdi Riahi, Karl Aberer, Paolo Papotti and Samuel H. Moseley. Their work appears in journals such as Proceedings of the VLDB Endowment, The VLDB Journal, ACM SIGMOD Record, IEEE Transactions on Software Engineering and ACM Transactions on Database Systems.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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