G. M. Smith
- Cognitive Neuroscience
- Mechanical Engineering
- Experimental and Cognitive Psychology
- Developmental and Educational Psychology
- Control and Systems Engineering
- Co-authors
- Michiko SakakiKou MurayamaVeronica X. YanR. W. HammingDouglas SaddyPeter GrindrodAlexander GrayL. H. Wasserman
- Topics
- Numerical Methods and Algorithms (3 papers)Bioinformatics and Genomic Networks (2 papers)Manufacturing Process and Optimization (1 paper)
- Cited by
- Cognitive NeuroscienceExperimental and Cognitive PsychologyDevelopmental and Educational Psychology
- Journals
- Mathematics of ComputationJournal of Experimental Psychology Learning Memory and CognitionJournal of Complex Networks
- Partner nations
- United KingdomUnited States
In The Last Decade
G. M. Smith
10 papers receiving 302 citations
Peers
Comparison fields: 5 of 114
- Cognitive Neuroscience 78
- Mechanical Engineering 47
- Experimental and Cognitive Psychology 44
- Developmental and Educational Psychology 37
- Control and Systems Engineering 34
Countries citing papers authored by G. M. Smith
This map shows the geographic impact of G. M. Smith'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 G. M. Smith with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites G. M. Smith more than expected).
Fields of papers citing papers by G. M. Smith
This network shows the impact of papers produced by G. M. Smith. 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 G. M. Smith. The network helps show where G. M. Smith may publish in the future.
Co-authorship network of co-authors of G. M. Smith
This figure shows the co-authorship network connecting the top 25 collaborators of G. M. Smith. A scholar is included among the top collaborators of G. M. Smith 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 G. M. Smith. G. M. Smith is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 103 | |
| 2 | Advanced feature selection methods in multinominal dementia classification from structural MRI data | 0 |
| 3 | Towards the computer-aided diagnosis of dementia based on the geometric and network connectivity of structural MRI data | 1 |
| 4 | 5 | |
| 5 | 1 | |
| 6 | Applied numerical methods for digital computation | 135 |
| 7 | Applied numerical methods for digital computation with FORTRAN and CSMP | 50 |
| 8 | Analog computer simulation of engineering systems | 3 |
| 9 | Applied numerical methods for digital computation with Fortran | 24 |
| 10 | 9 | |
| 11 | Advanced dynamics for engineers | 1 |
About G. M. Smith
G. M. Smith is a scholar working on Instrumentation, Computational Theory and Mathematics and Hardware and Architecture, having authored 11 papers that have together received 332 indexed citations. Recurring topics across this work include Numerical Methods and Algorithms (3 papers), Bioinformatics and Genomic Networks (2 papers) and Manufacturing Process and Optimization (1 paper). The work is most often cited by research in Cognitive Neuroscience (78 citations), Experimental and Cognitive Psychology (44 citations) and Developmental and Educational Psychology (37 citations). G. M. Smith has collaborated with scholars based in United Kingdom and United States. Frequent co-authors include Michiko Sakaki, Kou Murayama, Veronica X. Yan, R. W. Hamming, Douglas Saddy, Peter Grindrod, Alexander Gray, L. H. Wasserman, R. C. Nichol and Giuseppe Di Fatta. Their work appears in journals such as Mathematics of Computation, Journal of Experimental Psychology Learning Memory and Cognition and Journal of Complex Networks.
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.