Tabea Schwarz

838 citations
19 papers · 643 · h-index 11

Impact in

    • Advanced Data Storage Technologies
    • Caching and Content Delivery
    • Distributed systems and fault tolerance
    • Distributed and Parallel Computing Systems
    • Peer-to-Peer Network Technologies
    • Parallel Computing and Optimization Techniques

Papers in

Tabea Schwarz

19 papers receiving 594 citations

Peers

Tabea Schwarz
Comparison fields: 5 of 49
  • Computer Networks and Communications 534
  • Hardware and Architecture 110
  • Information Systems 188
  • Computer Vision and Pattern Recognition 93
  • Artificial Intelligence 107
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Citations per field
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Citations per year

Countries citing papers authored by Tabea Schwarz

Since Specialization
Citations

This map shows the geographic impact of Tabea Schwarz'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 Tabea Schwarz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tabea Schwarz more than expected).

Fields of papers citing papers by Tabea Schwarz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tabea Schwarz. 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 Tabea Schwarz. The network helps show where Tabea Schwarz may publish in the future.

Co-authors

The 18 scholars most cited alongside Tabea Schwarz, 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 Tabea Schwarz Line = papers co-authored together Tabea Schwarz links everyone, so they are left out of the graph.

All Works

19 of 19 papers shown
#Work
1 2003151
2 2004107
3 200573
4 200659
5 200448
6 200548
7 200437
8 200528
9 199519
10 200219
11 200319
12 199911
13 20057
14 20246
15 20023
16 20043
17 20022
18 20062
19 20041

About Tabea Schwarz

Tabea Schwarz is a scholar working on Computer Networks and Communications, Hardware and Architecture, Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing, having authored 19 papers that have together received 643 indexed citations. Recurring topics across this work include Advanced Data Storage Technologies (13 papers), Distributed systems and fault tolerance (6 papers), Caching and Content Delivery (6 papers), Parallel Computing and Optimization Techniques (5 papers), Algorithms and Data Compression (5 papers), Context-Aware Activity Recognition Systems (3 papers), Peer-to-Peer Network Technologies (2 papers) and Data Management and Algorithms (2 papers). The work is most often cited by research in Computer Networks and Communications (534 citations), Hardware and Architecture (110 citations), Information Systems (188 citations), Computer Vision and Pattern Recognition (93 citations) and Artificial Intelligence (107 citations). Tabea Schwarz has collaborated with scholars based in United States, Germany and France. Frequent co-authors include Ethan L. Miller, Qin Xin, Darrell D. E. Long, Witold Litwin, Scott Brandt, Daniela Nicklas, Walter A. Burkhard, Spencer W. Ng, Martin Bauer and Kristal T. Pollack. Their work appears in journals such as IEEE Transactions on Magnetics, eScholarship (California Digital Library) and Fachbereich Informatik (University of Stuttgart).

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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