Matthew Yee-King

484 total citations
35 papers, 226 citations indexed

About

Matthew Yee-King is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Artificial Intelligence. According to data from OpenAlex, Matthew Yee-King has authored 35 papers receiving a total of 226 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Computer Vision and Pattern Recognition, 15 papers in Signal Processing and 12 papers in Artificial Intelligence. Recurrent topics in Matthew Yee-King's work include Music Technology and Sound Studies (18 papers), Music and Audio Processing (15 papers) and Online Learning and Analytics (7 papers). Matthew Yee-King is often cited by papers focused on Music Technology and Sound Studies (18 papers), Music and Audio Processing (15 papers) and Online Learning and Analytics (7 papers). Matthew Yee-King collaborates with scholars based in United Kingdom, Australia and Italy. Matthew Yee-King's co-authors include Mark d’Inverno, Jon McCormack, Toby Gifford, Martin M. Roth, Mick Grierson, Harry Brenton, Mohammad Majid al‐Rifaie, Tim Blackwell, Roberto Confalonieri and Dave de Jonge and has published in prestigious journals such as SHILAP Revista de lepidopterología, Engineering Applications of Artificial Intelligence and Journal of the Audio Engineering Society.

In The Last Decade

Matthew Yee-King

31 papers receiving 209 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Matthew Yee-King United Kingdom 8 105 66 65 47 45 35 226
Theophanis Tsandilas France 10 138 1.3× 43 0.7× 63 1.0× 42 0.9× 133 3.0× 21 323
Gregor Rozinaj Slovakia 7 82 0.8× 45 0.7× 71 1.1× 12 0.3× 41 0.9× 69 242
Paraskevi Tzouveli Greece 9 100 1.0× 26 0.4× 91 1.4× 30 0.6× 48 1.1× 29 299
Laurissa Tokarchuk United Kingdom 11 51 0.5× 37 0.6× 80 1.2× 22 0.5× 50 1.1× 54 313
Arghir-Nicolae Moldovan Ireland 12 159 1.5× 58 0.9× 49 0.8× 28 0.6× 21 0.5× 30 456
Bryan Wang United States 11 107 1.0× 26 0.4× 98 1.5× 49 1.0× 112 2.5× 26 357
Lucio Ieronutti Italy 9 146 1.4× 25 0.4× 59 0.9× 27 0.6× 93 2.1× 17 313
Neşe Alyüz Türkiye 10 259 2.5× 119 1.8× 62 1.0× 30 0.6× 20 0.4× 30 409
Ralph Niels Netherlands 10 160 1.5× 23 0.3× 76 1.2× 48 1.0× 91 2.0× 16 305
Saeed Shafiee Sabet Norway 11 143 1.4× 19 0.3× 60 0.9× 32 0.7× 64 1.4× 37 290

Countries citing papers authored by Matthew Yee-King

Since Specialization
Citations

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

Fields of papers citing papers by Matthew Yee-King

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Matthew Yee-King. 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 Matthew Yee-King. The network helps show where Matthew Yee-King may publish in the future.

Co-authorship network of co-authors of Matthew Yee-King

This figure shows the co-authorship network connecting the top 25 collaborators of Matthew Yee-King. A scholar is included among the top collaborators of Matthew Yee-King 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 Matthew Yee-King. Matthew Yee-King is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
2.
d’Inverno, Mark, et al.. (2022). Explainable Computational Creativity. Goldsmiths (University of London). 334–341. 3 indexed citations
4.
McCormack, Jon, et al.. (2020). Design Considerations for Real-Time Collaboration with Creative Artificial Intelligence. Organised Sound. 25(1). 41–52. 40 indexed citations
5.
Yee-King, Matthew, et al.. (2019). Measuring the Impact of Level of Detail for Environmental Soundscapes in Digital Games. Journal of the Audio Engineering Society. 3 indexed citations
6.
Gifford, Toby, et al.. (2018). Computational systems for music improvisation. Digital Creativity. 29(1). 19–36. 16 indexed citations
7.
Grierson, Mick, et al.. (2017). Write once run anywhere revisited: machine learning and audio tools in the browser with C++ and emscripten. Goldsmiths (University of London). 3 indexed citations
8.
Yee-King, Matthew, Mick Grierson, & Mark d’Inverno. (2017). STEAM WORKS: Student coders experiment more and experimenters gain higher grades. 359–366. 8 indexed citations
9.
al‐Rifaie, Mohammad Majid, Matthew Yee-King, & Mark d’Inverno. (2016). Investigating Swarm Intelligence for Performance Prediction.. Goldsmiths (University of London). 264–269. 2 indexed citations
10.
Yee-King, Matthew & Mark d’Inverno. (2016). Experience driven design of creative systems. Goldsmiths (University of London). 85–92. 10 indexed citations
11.
Yee-King, Matthew & Mark d’Inverno. (2016). Stimulating collaborative activity in online social learning environments with Markov decision processes. Educational Data Mining. 652–653. 4 indexed citations
12.
Yee-King, Matthew. (2016). The Use of Interactive Genetic Algorithms in Sound Design: A Comparison Study. Goldsmiths (University of London). 1 indexed citations
13.
Gillies, Marco, et al.. (2015). Sketches vs skeletons. Goldsmiths (University of London). 104–111. 5 indexed citations
14.
Yee-King, Matthew, et al.. (2014). Designing Educational Social Machines for Effective Feedback.. International Association for Development of the Information Society. 2014(1). 7 indexed citations
15.
Yee-King, Matthew, Mark d’Inverno, & Pablo Noriega. (2014). Social machines for education driven by feedback agents. DIGITAL.CSIC (Spanish National Research Council (CSIC)). 1 indexed citations
16.
Yee-King, Matthew, Roberto Confalonieri, Carles Sierra, et al.. (2013). WeCurate. View. 571–576. 2 indexed citations
17.
Roth, Martin M. & Matthew Yee-King. (2011). A Comparison of Parametric Optimization Techniques for Musical Instrument Tone Matching. Journal of the Audio Engineering Society. 8 indexed citations
18.
Yee-King, Matthew. (2011). An autonomous timbre matching improviser.. The Journal of the Abraham Lincoln Association. 2011. 3 indexed citations
19.
Grierson, Mick, Chris Kiefer, & Matthew Yee-King. (2011). Progress Report on the EAVI BCI Toolkit for Music: Musical Applications of Algorithms for use with consumer brain computer interfaces. Sussex Research Online (University of Sussex). 2011. 4 indexed citations
20.
Yee-King, Matthew & Martin M. Roth. (2009). SYNTHBOT: AN UNSUPERVISED SOFTWARE SYNTHESIZER PROGRAMMER. The Journal of the Abraham Lincoln Association. 2008. 11 indexed citations

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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