Ciaran McCreesh

609 total citations
21 papers, 144 citations indexed

About

Ciaran McCreesh is a scholar working on Computer Networks and Communications, Artificial Intelligence and Computational Theory and Mathematics. According to data from OpenAlex, Ciaran McCreesh has authored 21 papers receiving a total of 144 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Computer Networks and Communications, 11 papers in Artificial Intelligence and 9 papers in Computational Theory and Mathematics. Recurrent topics in Ciaran McCreesh's work include Constraint Satisfaction and Optimization (13 papers), Graph Theory and Algorithms (7 papers) and Complexity and Algorithms in Graphs (5 papers). Ciaran McCreesh is often cited by papers focused on Constraint Satisfaction and Optimization (13 papers), Graph Theory and Algorithms (7 papers) and Complexity and Algorithms in Graphs (5 papers). Ciaran McCreesh collaborates with scholars based in United Kingdom, Denmark and Sweden. Ciaran McCreesh's co-authors include Patrick Prosser, Christine Solnon, R. Hoffmann, Robert Stewart, Phil Trinder, Jakob Nordstr”öm, Blair Archibald, Patrick Maier, David R. White and Jeremy Singer and has published in prestigious journals such as Autonomous Robots, Journal of Parallel and Distributed Computing and Journal of Artificial Intelligence Research.

In The Last Decade

Ciaran McCreesh

21 papers receiving 139 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Ciaran McCreesh United Kingdom 7 84 76 53 51 23 21 144
Kalikinkar Mandal Canada 9 132 1.6× 34 0.4× 35 0.7× 57 1.1× 16 0.7× 23 183
Soheil Behnezhad United States 8 63 0.8× 56 0.7× 83 1.6× 43 0.8× 26 1.1× 25 152
Amr Elmasry Egypt 7 83 1.0× 50 0.7× 91 1.7× 15 0.3× 21 0.9× 55 180
Paolo Giulio Franciosa Italy 7 54 0.6× 67 0.9× 62 1.2× 38 0.7× 58 2.5× 26 162
Stephen M. Majercik United States 8 220 2.6× 78 1.0× 60 1.1× 13 0.3× 16 0.7× 16 253
Jérémy Jean France 10 208 2.5× 27 0.4× 17 0.3× 100 2.0× 23 1.0× 22 228
Daniel K. Blandford United States 7 127 1.5× 90 1.2× 31 0.6× 57 1.1× 66 2.9× 10 211
Peter van Emde Boas Netherlands 9 120 1.4× 78 1.0× 128 2.4× 24 0.5× 25 1.1× 25 229
Miquel Ferrer Spain 8 109 1.3× 22 0.3× 31 0.6× 139 2.7× 48 2.1× 18 190
Gaëtan Leurent France 7 213 2.5× 34 0.4× 26 0.5× 106 2.1× 44 1.9× 22 247

Countries citing papers authored by Ciaran McCreesh

Since Specialization
Citations

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

Fields of papers citing papers by Ciaran McCreesh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ciaran McCreesh

This figure shows the co-authorship network connecting the top 25 collaborators of Ciaran McCreesh. A scholar is included among the top collaborators of Ciaran McCreesh based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Ciaran McCreesh. Ciaran McCreesh is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Bogaerts, Bart, et al.. (2023). Certified Dominance and Symmetry Breaking for Combinatorial Optimisation. Journal of Artificial Intelligence Research. 77. 1 indexed citations
2.
Bogaerts, Bart, et al.. (2022). Certified Symmetry and Dominance Breaking for Combinatorial Optimisation. Proceedings of the AAAI Conference on Artificial Intelligence. 36(4). 3698–3707. 3 indexed citations
3.
Fichte, Johannes K., et al.. (2021). Complications for Computational Experiments from Modern Processors. DROPS (Schloss Dagstuhl – Leibniz Center for Informatics). 3 indexed citations
4.
McCreesh, Ciaran & Patrick Prosser. (2021). Finding Maximum k-Cliques Faster Using Lazy Global Domination. Proceedings of the International Symposium on Combinatorial Search. 7(1). 72–80. 2 indexed citations
5.
Archibald, Blair, et al.. (2021). Practical Bigraphs via Subgraph Isomorphism. DROPS (Schloss Dagstuhl – Leibniz Center for Informatics). 17. 1 indexed citations
6.
McCreesh, Ciaran, et al.. (2021). Solving Graph Homomorphism and Subgraph Isomorphism Problems Faster Through Clique Neighbourhood Constraints. ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam). 1396–1402. 2 indexed citations
7.
McCreesh, Ciaran, et al.. (2020). Justifying All Differences Using Pseudo-Boolean Reasoning. Proceedings of the AAAI Conference on Artificial Intelligence. 34(2). 1486–1494. 4 indexed citations
8.
McCreesh, Ciaran, et al.. (2020). Subgraph Isomorphism Meets Cutting Planes: Solving With Certified Solutions. ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam). 1134–1140. 3 indexed citations
9.
Cano, José, et al.. (2018). Solving the task variant allocation problem in distributed robotics. Autonomous Robots. 42(7). 1477–1495. 9 indexed citations
10.
McCreesh, Ciaran, et al.. (2018). When Subgraph Isomorphism is Really Hard, and Why This Matters for Graph Databases. Journal of Artificial Intelligence Research. 61. 723–759. 25 indexed citations
11.
Gent, Ian P., et al.. (2018). A review of literature on parallel constraint solving. Theory and Practice of Logic Programming. 18(5-6). 725–758. 1 indexed citations
12.
Archibald, Blair, Patrick Maier, Ciaran McCreesh, Robert Stewart, & Phil Trinder. (2017). Replicable parallel branch and bound search. Journal of Parallel and Distributed Computing. 113. 92–114. 14 indexed citations
13.
Hoffmann, R., et al.. (2017). Between Subgraph Isomorphism and Maximum Common Subgraph. Proceedings of the AAAI Conference on Artificial Intelligence. 31(1). 11 indexed citations
14.
McCreesh, Ciaran. (2016). Solving hard subgraph problems in parallel. International Joint Conference on Artificial Intelligence. 4014–4015. 3 indexed citations
15.
McCreesh, Ciaran, et al.. (2016). Heuristics and really hard instances for subgraph isomorphism problems. ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam). 631–638. 6 indexed citations
16.
Cano, José, et al.. (2016). Task Variant Allocation in Distributed Robotics. ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam). 4 indexed citations
17.
McCreesh, Ciaran & Patrick Prosser. (2015). The Shape of the Search Tree for the Maximum Clique Problem and the Implications for Parallel Branch and Bound. ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam). 2(1). 1–27. 16 indexed citations
18.
Arabas, Sylwester, Ian P. Gent, Tristan Henderson, et al.. (2014). An Open and Reproducible Paper on Openness and Reproducibility of Papers in Computational Science.. 3 indexed citations
19.
McCreesh, Ciaran & Patrick Prosser. (2014). A parallel branch and bound algorithm for the maximum labelled clique problem. Optimization Letters. 9(5). 949–960. 3 indexed citations
20.
McCreesh, Ciaran & Patrick Prosser. (2013). Multi-Threading a State-of-the-Art Maximum Clique Algorithm. Algorithms. 6(4). 618–635. 22 indexed citations

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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