Andrew H. Fagg

3.6k citations
89 papers · 2.5k indexed · h-index 24

Andrew H. Fagg

86 papers receiving 2.3k citations

Peers

Andrew H. Fagg
Comparison fields: 5 of 106
  • Cognitive Neuroscience 1.4k
  • Social Psychology 529
  • Control and Systems Engineering 587
  • Neurology 178
  • Cellular and Molecular Neuroscience 369
Replace Daniel Bullock with:
Daniel Bullock United States
Stan Gielen Netherlands
Luis Montesano Spain
Vittorio Sanguineti Italy
Peter Ford Dominey France
Li‐Wei Ko Taiwan
Jiping He United States
G.F. Inbar Israel
Rieko Osu Japan
James W. Bisley United States
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Citations per field
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Citations per year

Countries citing papers authored by Andrew H. Fagg

Since Specialization
Citations

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

Fields of papers citing papers by Andrew H. Fagg

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Andrew H. Fagg. 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 Andrew H. Fagg. The network helps show where Andrew H. Fagg may publish in the future.

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20241
2 20233
3 20220
4 201713
5 201614
6
Robotic Crawling Assistance for Infants with Cerebral Palsy.
20153
7 201332
8 20122
9 200967
10 20096
11 200747
12
Constructing Robust Neural Decoders Using Limited Training Data
20071
13
Improving Grasp Skills Using Schema Structured Learning
200611
14
Remote supervisory control of a humanoid robot
20051
15
Active learning for robot manipulation
20045
16
Robot Learning with Predictions of Operator Intent.
20041
17
Synthetic PET imaging for grasping: from primate Neurophysiology to human behavior
200311
18
A Framework For Humanoid Control and Intelligence
200310
19 19964
20 199432

About Andrew H. Fagg

Andrew H. Fagg is a scholar working on Cognitive Neuroscience, Control and Systems Engineering and Cellular and Molecular Neuroscience, having authored 89 papers that have together received 2.5k indexed citations. Recurring topics across this work include Robot Manipulation and Learning (28 papers), Reinforcement Learning in Robotics (18 papers), EEG and Brain-Computer Interfaces (17 papers), Motor Control and Adaptation (15 papers), Neural dynamics and brain function (15 papers), Neuroscience and Neural Engineering (14 papers), Muscle activation and electromyography studies (12 papers) and Robotic Path Planning Algorithms (9 papers). The work is most often cited by research in Cognitive Neuroscience (1.4k citations), Social Psychology (529 citations) and Control and Systems Engineering (587 citations). Andrew H. Fagg has collaborated with scholars based in United States, Spain and United Kingdom. Frequent co-authors include Michael A. Arbib, Scott T. Grafton, Roderic A. Grupen, Robert W. Platt, Nicholas G. Hatsopoulos, Brian Neil Levine, James Davis, Andrew G. Barto, Roger P. Woods and Aaron J. Suminski. Their work appears in journals such as Nature Communications, Journal of Neuroscience and SHILAP Revista de lepidopterología.

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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