Duncan Williams

975 citations
47 papers · 541 indexed · h-index 14

Impact in

    • EEG and Brain-Computer Interfaces
    • Neuroscience and Music Perception
    • Neural dynamics and brain function
    • Functional Brain Connectivity Studies
  • Music top 5%

Papers in

Duncan Williams

44 papers receiving 519 citations

Peers

Duncan Williams
Comparison fields: 5 of 92
  • Cognitive Neuroscience 378
  • Music 44
  • Signal Processing 125
  • Experimental and Cognitive Psychology 127
  • Computer Vision and Pattern Recognition 100
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Citations per year

Countries citing papers authored by Duncan Williams

Since Specialization
Citations

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

Fields of papers citing papers by Duncan Williams

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown
#Work
1 202251
2 20223
3 202015
4 202015
5 201950
6 20184
7 201715
8 20161
9 20164
10
Multi-Criteria Decision Aid Analysis of a Musification Approach to the Auditory Display of Micro-Organism Movement
20151
11
Affective Potential in Vocal Production
20151
12 201513
13 201534
14 20155
15
AFFECTIVE JUKEBOX: A CONFIRMATORY STUDY OF EEG EMOTIONAL CORRELATES IN RESPONSE TO MUSICAL STIMULI
20148
16 20143
17
Towards Affective Algorithmic Composition
20136
18
Perceptually-Motivated Audio Morphing: Warmth
20109
19
Perceptually-motivated audio morphing: softness
20097
20
Perceptually-Motivated Audio Morphing: Brightness
200713

About Duncan Williams

Duncan Williams is a scholar working on Cognitive Neuroscience, Signal Processing, Experimental and Cognitive Psychology, Music and Computer Vision and Pattern Recognition, having authored 47 papers that have together received 541 indexed citations. Recurring topics across this work include Neuroscience and Music Perception (24 papers), Music Technology and Sound Studies (14 papers), Neural dynamics and brain function (13 papers), EEG and Brain-Computer Interfaces (12 papers), Music and Audio Processing (11 papers), Emotion and Mood Recognition (8 papers), Multisensory perception and integration (6 papers) and Music Therapy and Health (5 papers). The work is most often cited by research in Cognitive Neuroscience (378 citations), Music (44 citations), Signal Processing (125 citations), Experimental and Cognitive Psychology (127 citations) and Computer Vision and Pattern Recognition (100 citations). Duncan Williams has collaborated with scholars based in United Kingdom, United States and Cyprus. Frequent co-authors include Eduardo Reck Miranda, Alexis Kirke, Ian Daly, Slawomir J. Nasuto, Faustina Hwang, Asad Malik, Etienne B. Roesch, Tim Brookes, Joanna Hodge and J. A. Eaton. Their work appears in journals such as Journal of the Audio Engineering Society, ACM Transactions on Applied Perception, PLoS ONE, Scientific Reports and Psychology of Music.

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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