Michael Dewar

540 citations
12 papers · 371 · h-index 9

Impact in

Papers in

    • RNA Interference and Gene Delivery 2
    • Advanced biosensing and bioanalysis techniques 2
    • Chemical Synthesis and Analysis 2
    • Bayesian Methods and Mixture Models 1
    • Intelligent Tutoring Systems and Adaptive Learning 1

Michael Dewar

12 papers receiving 356 citations

Peers

Michael Dewar
Comparison fields: 5 of 101
  • Cognitive Neuroscience 73
  • Developmental and Educational Psychology 46
  • Communication 25
  • Applied Mathematics 22
  • Statistical and Nonlinear Physics 26
Replace Roland Schäfer with:
Roland Schäfer Germany
Bryan R. Gibson United States
Gabriel Altmann Germany
Daniel Hardt Denmark
Nurul Fazmidar Binti Mohd Noor Malaysia
Eli Maor United States
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Joe Jackson United States
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Michael Dewar relative to Roland Schäfer Germany Roland Schäfer's profile →
Citations per field
00.5×4.2×
Roland Schäfer · 1×
Citations per year

Countries citing papers authored by Michael Dewar

Since Specialization
Citations

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

Fields of papers citing papers by Michael Dewar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 20 scholars most cited alongside Michael Dewar, 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 Michael Dewar Line = papers co-authored together Michael Dewar links everyone, so they are left out of the graph.

All Works

12 of 12 papers shown
#Work
1 201381
2 201279
3 201149
4 201333
5 200828
6 201126
7 201024
8 200718
9 200818
10 20117
11 20116
12
Testing theories of skill learning using a very large sample of online game players
20132

About Michael Dewar

Michael Dewar is a scholar working on Molecular Biology, Artificial Intelligence, Developmental and Educational Psychology, Statistics and Probability and Communication, having authored 12 papers that have together received 371 indexed citations. Recurring topics across this work include RNA Interference and Gene Delivery (2 papers), Advanced biosensing and bioanalysis techniques (2 papers), Chemical Synthesis and Analysis (2 papers), Statistical Methods and Bayesian Inference (2 papers), Child and Animal Learning Development (2 papers), Bayesian Methods and Mixture Models (1 paper), Point processes and geometric inequalities (1 paper) and Intelligent Tutoring Systems and Adaptive Learning (1 paper). The work is most often cited by research in Cognitive Neuroscience (73 citations), Developmental and Educational Psychology (46 citations), Communication (25 citations), Applied Mathematics (22 citations) and Statistical and Nonlinear Physics (26 citations). Michael Dewar has collaborated with scholars based in United Kingdom, United States and Malta. Frequent co-authors include Visakan Kadirkamanathan, Tom Stafford, Guido Sanguinetti, Andrew Zammit‐Mangion, David B. Grayden, Dean R. Freestone, Henry Farrell, Deen Freelon, Sean Aday and John Sides. Their work appears in journals such as IEEE Transactions on Signal Processing, BMC Systems Biology, Psychological Science, Angewandte Chemie International Edition and American Behavioral Scientist.

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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