Thomas Stibor
Impact in
- Biomedical Engineering top 10%
- Artificial Immune Systems Applications
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- T-cell and B-cell Immunology
Papers in
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- Artificial Immune Systems Applications 9
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- Anomaly Detection Techniques and Applications 5
- Co-authors
- Jon Timmis (7 shared papers)Edward Clark (1 shared paper)Andrew N. W. Hone (1 shared paper)Claudia Eckert (4 shared papers)Han Xiao (2 shared papers)Graham Kendall (1 shared paper)Jonathan M. Garibaldi (1 shared paper)Xiao Han (1 shared paper)
- Journals
- Natural Computing (1 paper)Theoretical Computer Science (1 paper)Lecture notes in computer science (1 paper)it - Information Technology (1 paper)EPJ Web of Conferences (1 paper)
- Partner nations
- GermanyUnited KingdomItaly
In The Last Decade
Thomas Stibor
13 papers receiving 397 citations
Peers
Comparison fields: 5 of 72
- Biomedical Engineering 304
- Immunology 102
- Signal Processing 47
- Artificial Intelligence 137
- Computer Networks and Communications 79
Countries citing papers authored by Thomas Stibor
This map shows the geographic impact of Thomas Stibor'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 Thomas Stibor with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Thomas Stibor more than expected).
Fields of papers citing papers by Thomas Stibor
This network shows the impact of papers produced by Thomas Stibor. 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 Thomas Stibor. The network helps show where Thomas Stibor may publish in the future.
Co-authors
The 10 scholars most cited alongside Thomas Stibor, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2008 | 193 | |
| 2 | 2005 | 121 | |
| 3 | 2005 | 27 | |
| 4 | Efficient Collapsed Gibbs Sampling For Latent Dirichlet Allocation | 2010 | 24 |
| 5 | 2007 | 13 | |
| 6 | 2009 | 10 | |
| 7 | 2008 | 10 | |
| 8 | 2006 | 9 | |
| 9 | 2007 | 8 | |
| 10 | 2011 | 7 | |
| 11 | 2010 | 6 | |
| 12 | Toward Artificial Synesthesia: Linking Images and Sounds via Words | 2013 | 3 |
| 13 | 2006 | 1 | |
| 14 | 2011 | 1 | |
| 15 | 2020 | 0 |
About Thomas Stibor
Thomas Stibor is a scholar working on Biomedical Engineering, Artificial Intelligence, Computer Networks and Communications, Molecular Biology and Signal Processing, having authored 15 papers that have together received 433 indexed citations. Recurring topics across this work include Artificial Immune Systems Applications (9 papers), Anomaly Detection Techniques and Applications (5 papers), T-cell and B-cell Immunology (3 papers), Advanced Malware Detection Techniques (3 papers), Network Security and Intrusion Detection (3 papers), Gene Regulatory Network Analysis (2 papers), Hermeneutics and Narrative Identity (1 paper) and Health, Medicine and Society (1 paper). The work is most often cited by research in Biomedical Engineering (304 citations), Immunology (102 citations), Signal Processing (47 citations), Artificial Intelligence (137 citations) and Computer Networks and Communications (79 citations). Thomas Stibor has collaborated with scholars based in Germany, United Kingdom and Italy. Frequent co-authors include Jon Timmis, Edward Clark, Andrew N. W. Hone, Claudia Eckert, Han Xiao, Graham Kendall, Jonathan M. Garibaldi, Xiao Han, Giuseppe Nicosia and J. Adamczewski-Musch. Their work appears in journals such as Natural Computing, Theoretical Computer Science, Lecture notes in computer science, it - Information Technology and EPJ Web of Conferences.
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.