Michael Brady

435 citations
11 papers · 247 · h-index 4

Impact in

Papers in

Michael Brady

8 papers receiving 201 citations

Peers

Michael Brady
Comparison fields: 5 of 54
  • Artificial Intelligence 153
  • General Decision Sciences 7
  • Computer Vision and Pattern Recognition 62
  • Management Science and Operations Research 37
  • Computer Networks and Communications 57
Replace Shi-Jim Yen with:
Shi-Jim Yen Taiwan
Jaime Carbonell United States
Matthias Baumgarten United Kingdom
Dmitri Asonov United States
Hanshu Hong China
Ruimin Wang China
Akshay Agrawal United States
Timothy Mann United States
Norman Carver United States
Michael Brady relative to Shi-Jim Yen Taiwan Shi-Jim Yen's profile →
Citations per field
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Shi-Jim Yen · 1×
Citations per year

Countries citing papers authored by Michael Brady

Since Specialization
Citations

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

Fields of papers citing papers by Michael Brady

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 12 scholars most cited alongside Michael Brady, 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 Brady Line = papers co-authored together Michael Brady links everyone, so they are left out of the graph.

All Works

11 of 11 papers shown
#Work
1 1991205
2 199028
3 19944
4 20063
5
Speech as a problem of motor control in robotics
20092
6 20142
7
A Neural Field Model of Word Repetition Effects in Early Time-Course ERPs in Spoken Word Perception.
20161
8 20101
9 20011
10
A Low Cost Desktop Robot and Tele-Presence Device for Interactive Speech Research.
20160
11 20140

About Michael Brady

Michael Brady is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Cognitive Neuroscience, Signal Processing and Experimental and Cognitive Psychology, having authored 11 papers that have together received 247 indexed citations. Recurring topics across this work include Speech and dialogue systems (3 papers), Speech Recognition and Synthesis (2 papers), Phonetics and Phonology Research (2 papers), Speech and Audio Processing (2 papers), Linguistic Variation and Morphology (1 paper), AI-based Problem Solving and Planning (1 paper), Advanced Vision and Imaging (1 paper) and Reading and Literacy Development (1 paper). The work is most often cited by research in Artificial Intelligence (153 citations), General Decision Sciences (7 citations), Computer Vision and Pattern Recognition (62 citations), Management Science and Operations Research (37 citations) and Computer Networks and Communications (57 citations). Michael Brady has collaborated with scholars based in United States and United Kingdom. Frequent co-authors include Daniel G. Bobrow, Randall Davis, Stuart Russell, David W. Murray, Huosheng Hu, Robert F. Port, Stephen M. Smith, Matthias Scheutz, Andrew M. Olney and Martin Nystrand. Their work appears in journals such as The Journal of the Acoustical Society of America, Cognitive Science, NeuroImage, eScholarship (California Digital Library) and Procedia Computer Science.

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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