Stephan Schulz

23 papers receiving 524 citations

Peers

Stephan Schulz
Comparison fields: 5 of 92
  • Software 29
  • Artificial Intelligence 242
  • Computational Theory and Mathematics 109
  • Theoretical Computer Science 6
  • Immunology 75
Replace Jeffrey E. Miller with:
Jeffrey E. Miller United States
Zhi Guo China
Matthew Poole United Kingdom
Daniele Ramazzotti Italy
Julie Bachmann Germany
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Marco Chierici Italy
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Stephan Schulz relative to Jeffrey E. Miller United States Jeffrey E. Miller's profile →
Citations per field
00.5×6.8×
Jeffrey E. Miller · 1×
Citations per year

Countries citing papers authored by Stephan Schulz

Since Specialization
Citations

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

Fields of papers citing papers by Stephan Schulz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Stephan Schulz, 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 Stephan Schulz Line = papers co-authored together Stephan Schulz links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.

#Work
1
E - a brainiac theorem prover
2002174
2 201452
3 201235
4 200934
5
TSTP Data-Exchange Formats for Automated Theorem Proving Tools
200433
6 200432
7 201130
8 200030
9 201229
10 200428
11 201420
12 200117
13 201315
14
Learning Search Control Knowledge for Equational Deduction
200010
15 20098
16 20186
17
[Molecular diagnosis of mycobacterial infections].
20075
18 20004
19 20061
20 20051

About Stephan Schulz

Stephan Schulz is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Immunology, Hematology and Genetics, having authored 23 papers that have together received 567 indexed citations. Recurring topics across this work include Logic, programming, and type systems (4 papers), Immunotherapy and Immune Responses (4 papers), Formal Methods in Verification (4 papers), Chronic Lymphocytic Leukemia Research (3 papers), CAR-T cell therapy research (3 papers), Hematopoietic Stem Cell Transplantation (3 papers), Microbial Community Ecology and Physiology (3 papers) and T-cell and B-cell Immunology (3 papers). The work is most often cited by research in Software (29 citations), Artificial Intelligence (242 citations), Computational Theory and Mathematics (109 citations), Theoretical Computer Science (6 citations) and Immunology (75 citations). Stephan Schulz has collaborated with scholars based in Germany, United States and Netherlands. Frequent co-authors include Geoff Sutcliffe, Falko Fend, Martin Werner, Marcus Kremer, Michael Schloter, Antonello D. Cabras, Carsten Linnemann, Ton N. Schumacher, Laura Bies and Lukas Y. Wick. Their work appears in journals such as The ISME Journal, Blood, Molecular Therapy, Journal of Physics B Atomic Molecular and Optical Physics and BMC Medicine.

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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