Ben McKay

847 citations
26 papers · 587 indexed · h-index 13

Impact in

Papers in

Ben McKay

24 papers receiving 556 citations

Peers

Ben McKay
Comparison fields: 5 of 86
  • Computational Theory and Mathematics 222
  • Control and Systems Engineering 113
  • Artificial Intelligence 138
  • Spectroscopy 48
  • Materials Chemistry 124
Replace Travis Hart with:
Travis Hart United States
Pieter Plehiers Belgium
Nicholas Holmes United Kingdom
Connor J. Taylor United Kingdom
Manuel Dahmen Germany
Jamie A. Manson United Kingdom
Adam D. Clayton United Kingdom
Seif‐Eddeen K. Fateen Egypt
Federico Galvanin United Kingdom
Vishnu H Nair Switzerland
Ben McKay relative to Travis Hart United States Travis Hart's profile →
Citations per field
00.5×1.6×
Travis Hart · 1×
Citations per year

Countries citing papers authored by Ben McKay

Since Specialization
Citations

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

Fields of papers citing papers by Ben McKay

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 200636
2 20061
3 200513
4 200510
5 200425
6 20044
7 200434
8 2004129
9 200311
10 200315
11 20020
12
Non-linear continuum regression using genetic programming
19999
13 19989
14 1997105
15 199716
16
Dynamic Modelling of a Cooking Extruder
19963
17 199614
18 19967
19
Industrial Applications of MATLAB Based Software for Advanced Data Analysis and Control
19951
20 19791

About Ben McKay

Ben McKay is a scholar working on Control and Systems Engineering, Computational Theory and Mathematics, Fluid Flow and Transfer Processes, Spectroscopy and Artificial Intelligence, having authored 26 papers that have together received 587 indexed citations. Recurring topics across this work include Advanced Control Systems Optimization (7 papers), Computational Drug Discovery Methods (6 papers), Evolutionary Algorithms and Applications (6 papers), Fault Detection and Control Systems (5 papers), Machine Learning in Materials Science (4 papers), Analytical Chemistry and Chromatography (4 papers), Process Optimization and Integration (4 papers) and Viral Infectious Diseases and Gene Expression in Insects (3 papers). The work is most often cited by research in Computational Theory and Mathematics (222 citations), Control and Systems Engineering (113 citations), Artificial Intelligence (138 citations), Spectroscopy (48 citations) and Materials Chemistry (124 citations). Ben McKay has collaborated with scholars based in Australia, United Kingdom and Germany. Frequent co-authors include Johann Gasteiger, Nathan Brown, Mark J. Willis, Geoffrey W. Barton, François Gilardoni, Erik‐Jan Ras, Gadi Rothenberg, Alan A. Smith, Eric W. P. Damen and Marcel Hoogenraad. Their work appears in journals such as Computers & Chemical Engineering, Journal of Computer-Aided Molecular Design, Tetrahedron Asymmetry, Organic Process Research & Development and Theriogenology.

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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