David Gabelaia

539 citations
18 papers · 216 · h-index 8

Impact in

Papers in

David Gabelaia

18 papers receiving 201 citations

Peers

David Gabelaia
Comparison fields: 5 of 33
  • Computational Theory and Mathematics 145
  • Artificial Intelligence 174
  • Software 13
  • Signal Processing 24
  • Computer Networks and Communications 46
Replace Irène Guessarian with:
Irène Guessarian France
Lauri Hella Finland
Christian G. Fermüller Austria
Herman Geuvers Netherlands
Isolde Adler Germany
Horst Reichel Germany
Varmo Vene Estonia
Massimiliano Goldwurm Italy
Agi Kurucz United Kingdom
Matthieu Sozeau France
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Citations per field
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Citations per year

Countries citing papers authored by David Gabelaia

Since Specialization
Citations

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

Fields of papers citing papers by David Gabelaia

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 15 scholars most cited alongside David Gabelaia, 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 David Gabelaia Line = papers co-authored together David Gabelaia links everyone, so they are left out of the graph.

All Works

18 of 18 papers shown
#Work
1 200542
2 201032
3 200532
4 200523
5 200617
6
Computational Complexity of Spatio-Temporal Logics
200316
7 200914
8 201310
9 20146
10 20105
11 20165
12 20224
13 20223
14 20133
15 20151
16 20191
17 20101
18
Products of `transitive' modal logics with constant and expanding domains
20041

About David Gabelaia

David Gabelaia is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Computer Networks and Communications, Mathematical Physics and Signal Processing, having authored 18 papers that have together received 216 indexed citations. Recurring topics across this work include Logic, Reasoning, and Knowledge (17 papers), Advanced Algebra and Logic (12 papers), Logic, programming, and type systems (7 papers), Constraint Satisfaction and Optimization (5 papers), semigroups and automata theory (3 papers), Formal Methods in Verification (3 papers), Semantic Web and Ontologies (2 papers) and Homotopy and Cohomology in Algebraic Topology (1 paper). The work is most often cited by research in Computational Theory and Mathematics (145 citations), Artificial Intelligence (174 citations), Software (13 citations), Signal Processing (24 citations) and Computer Networks and Communications (46 citations). David Gabelaia has collaborated with scholars based in United States, United Kingdom and Georgia. Frequent co-authors include Guram Bezhanishvili, Frank Wolter, Michael Zakharyaschev, Agi Kurucz, Roman Kontchakov, Nick Bezhanishvili, Alexander Kurz, Lev D. Beklemishev, Balder ten Cate and Mamuka Jibladze. Their work appears in journals such as Annals of Pure and Applied Logic, The Review of Symbolic Logic, Journal of Symbolic Logic, Studia Logica and Applied Categorical Structures.

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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