Nancy M. Amato

8.8k citations
221 papers · 5.3k indexed · h-index 40
Topics
Robotic Path Planning Algorithms (101 papers)Robotics and Sensor-Based Localization (61 papers)Computational Geometry and Mesh Generation (34 papers)

In The Last Decade

Nancy M. Amato

214 papers receiving 5.0k citations

Peers

Nancy M. Amato
Comparison fields: 5 of 116
  • Computer Vision and Pattern Recognition 3.3k
  • Aerospace Engineering 1.7k
  • Control and Systems Engineering 1.5k
  • Computer Networks and Communications 956
  • Artificial Intelligence 777
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Citations per field
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Citations per year

Countries citing papers authored by Nancy M. Amato

Since Specialization
Citations

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

Fields of papers citing papers by Nancy M. Amato

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Nancy M. Amato. 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 Nancy M. Amato. The network helps show where Nancy M. Amato may publish in the future.

Co-authorship network of co-authors of Nancy M. Amato

This figure shows the co-authorship network connecting the top 25 collaborators of Nancy M. Amato. A scholar is included among the top collaborators of Nancy M. Amato 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 Nancy M. Amato. Nancy M. Amato 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
#WorkIndexed citations
1 1
2 0
3 17
4 19
5 13
6 2
7 2
8
Rigidity analysis for protein motion and folding core identification
1
9
Efficient Massively Parallel Transport Sweeps
12
10
Metrics for sampling-based motion planning
1
11 147
12 36
13 94
14
Hole Avoidance: Experiments in Coordinated Motion on Rough Terrain
4
15
Bias-Optimal Incremental Learning of Control Sequences for Virtual Robots
2
16
Neuron Prm: A Framework for Constructing Cortical Networks
1
17 19
18 10
19
Computing the arrangement of curve segments: Divide-and-conquer algorithms via sampling
19
20
OBPRM: an obstacle-based PRM for 3D workspaces
301

About Nancy M. Amato

Nancy M. Amato is a scholar working on Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition and Hardware and Architecture, having authored 221 papers that have together received 5.3k indexed citations. Recurring topics across this work include Robotic Path Planning Algorithms (101 papers), Robotics and Sensor-Based Localization (61 papers) and Computational Geometry and Mesh Generation (34 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (587 citations), Computer Vision and Pattern Recognition (3.3k citations) and Aerospace Engineering (1.7k citations). Nancy M. Amato has collaborated with scholars based in United States, Mexico and Germany. Frequent co-authors include Jyh‐Ming Lien, Guang Song, O. Burçhan Bayazıt, Shawna Thomas, Lucia K. Dale, You Wu, Daniel Vallejo, Christopher A. Jones, Peter F. Stiller and Suman Chakravorty. Their work appears in journals such as Bioinformatics, Journal of Molecular Biology and Journal of Computational Physics.

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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