Conor McBride

2.9k citations
68 papers · 1.9k · h-index 24

Impact in

Papers in

Conor McBride

65 papers receiving 1.8k citations

Peers

Conor McBride
Comparison fields: 5 of 54
  • Computational Theory and Mathematics 1.0k
  • Artificial Intelligence 1.8k
  • Hardware and Architecture 356
  • Software 178
  • Information Systems 361
Replace Ross Paterson with:
Ross Paterson United Kingdom
Amr Sabry United States
Nick Benton United Kingdom
Eugenio Moggi Italy
Ralf Hinze Germany
Christine Paulin-Mohring France
Gavin Bierman United Kingdom
Roberto M. Amadio France
Matt Kaufmann United States
Sam Lindley United Kingdom
Conor McBride relative to Ross Paterson United Kingdom Ross Paterson's profile →
Citations per field
00.5×3.9×
Ross Paterson · 1×
Citations per year

Countries citing papers authored by Conor McBride

Since Specialization
Citations

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

Fields of papers citing papers by Conor McBride

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 24 scholars most cited alongside Conor McBride, 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 Conor McBride Line = papers co-authored together Conor McBride links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 68 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2007279
2 2004231
3 200285
4 200773
5 200372
6 201667
7 200567
8 200462
9 200255
10 201053
11 201343
12 201142
13 201339
14 201638
15 200635
16 200832
17 200331
18 200431
19
∂ for Data: Differentiating Data Structures
200430
20 201628

About Conor McBride

Conor McBride is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Computer Networks and Communications, Hardware and Architecture and Information Systems, having authored 68 papers that have together received 1.9k indexed citations. Recurring topics across this work include Logic, programming, and type systems (58 papers), Logic, Reasoning, and Knowledge (31 papers), Parallel Computing and Optimization Techniques (16 papers), Advanced Database Systems and Queries (14 papers), Formal Methods in Verification (14 papers), Software Engineering Research (10 papers), Computability, Logic, AI Algorithms (8 papers) and Advanced Software Engineering Methodologies (5 papers). The work is most often cited by research in Computational Theory and Mathematics (1.0k citations), Artificial Intelligence (1.8k citations), Hardware and Architecture (356 citations), Software (178 citations) and Information Systems (361 citations). Conor McBride has collaborated with scholars based in United Kingdom, Netherlands and Pakistan. Frequent co-authors include James McKinna, Ross Paterson, Thorsten Altenkirch, Sam Lindley, Peter Morris, Robert Atkey, Wouter Swierstra, James Chapman, Pierre-Évariste Dagand and Craig McLaughlin. Their work appears in journals such as ACM SIGPLAN Notices, Journal of Functional Programming, Lecture notes in computer science, Proceedings of the ACM on Programming Languages and Journal of Automated Reasoning.

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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