Tod Machover
Impact in
-
- Online Learning and Analytics
- Human-Computer Interaction top 5%
- Interactive and Immersive Displays
Papers in
- Music 2
- Diverse Music Education Insights 1
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- Music Technology and Sound Studies 11
- Video Analysis and Summarization 1
- Co-authors
- Walter BenderRosalind W. PicardDeb RoyBruce BlumbergCynthia BreazealCarol StroheckerDavid CavalloMitchel Resnick
- Journals
- Contemporary Music Review (2 papers)International Journal of Arts and Technology (1 paper)Science (1 paper)BT Technology Journal (2 papers)Zenodo (CERN European Organization for Nuclear Research) (4 papers)
- Partner nations
- United StatesJapan
In The Last Decade
Tod Machover
12 papers receiving 333 citations
Peers
Comparison fields: 5 of 81
- Computer Science Applications 74
- Human-Computer Interaction 75
- Developmental and Educational Psychology 86
- Computer Vision and Pattern Recognition 122
- Cognitive Neuroscience 112
Countries citing papers authored by Tod Machover
This map shows the geographic impact of Tod Machover'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 Tod Machover with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tod Machover more than expected).
Fields of papers citing papers by Tod Machover
This network shows the impact of papers produced by Tod Machover. 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 Tod Machover. The network helps show where Tod Machover may publish in the future.
Co-authors
The 20 scholars most cited alongside Tod Machover, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 1 | |
| 2 | 2017 | 1 | |
| 3 | 2016 | 3 | |
| 4 | 2015 | 0 | |
| 5 | 2015 | 2 | |
| 6 | 2004 | 279 | |
| 7 | 2004 | 23 | |
| 8 | 2003 | 1 | |
| 9 | Sparkler: An Audio-Driven Interactive Live Computer Performance for Symphony Orchestra | 2002 | 3 |
| 10 | 2002 | 14 | |
| 11 | 1996 | 0 | |
| 12 | Hyperinstruments: Musically Intelligent and Interactive Performance and Creativity Systems. | 1989 | 73 |
| 13 | Musical thought at IRCAM | 1984 | 2 |
| 14 | 1984 | 4 |
About Tod Machover
Tod Machover is a scholar working on Music, Computer Vision and Pattern Recognition, Signal Processing, Human-Computer Interaction and Cognitive Neuroscience, having authored 14 papers that have together received 406 indexed citations. Recurring topics across this work include Music Technology and Sound Studies (11 papers), Music and Audio Processing (5 papers), Neuroscience and Music Perception (3 papers), Interactive and Immersive Displays (2 papers), Tactile and Sensory Interactions (2 papers), Innovative Teaching and Learning Methods (1 paper), Diverse Music Education Insights (1 paper) and Video Analysis and Summarization (1 paper). The work is most often cited by research in Computer Science Applications (74 citations), Human-Computer Interaction (75 citations), Developmental and Educational Psychology (86 citations), Computer Vision and Pattern Recognition (122 citations) and Cognitive Neuroscience (112 citations). Tod Machover has collaborated with scholars based in United States and Japan. Frequent co-authors include Walter Bender, Rosalind W. Picard, Deb Roy, Bruce Blumberg, Cynthia Breazeal, Carol Strohecker, David Cavallo, Mitchel Resnick, Seymour Papert and Joe Paradiso. Their work appears in journals such as Contemporary Music Review, International Journal of Arts and Technology, Science, BT Technology Journal and Zenodo (CERN European Organization for Nuclear Research).
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.