Nadia Figueroa
About
In The Last Decade
Nadia Figueroa
40 papers receiving 614 citations
Peers
Comparison fields: 5 of 76
- Control and Systems Engineering 312
- Biomedical Engineering 205
- Computer Vision and Pattern Recognition 193
- Mechanical Engineering 125
- Cognitive Neuroscience 85
Countries citing papers authored by Nadia Figueroa
This map shows the geographic impact of Nadia Figueroa'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 Nadia Figueroa with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nadia Figueroa more than expected).
Fields of papers citing papers by Nadia Figueroa
This network shows the impact of papers produced by Nadia Figueroa. 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 Nadia Figueroa. The network helps show where Nadia Figueroa may publish in the future.
Co-authorship network of co-authors of Nadia Figueroa
This figure shows the co-authorship network connecting the top 25 collaborators of Nadia Figueroa. A scholar is included among the top collaborators of Nadia Figueroa 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 Nadia Figueroa. Nadia Figueroa is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 3 | |
| 6 | 3 | |
| 7 | 1 | |
| 8 | 2 | |
| 9 | 2 | |
| 10 | 0 | |
| 11 | 32 | |
| 12 | 0 | |
| 13 | 15 | |
| 14 | 18 | |
| 15 | A Physically-Consistent Bayesian Non-Parametric Mixture Model for Dynamical System Learning. | 15 |
| 16 | Learning Complex Manipulation Tasks from Heterogeneous and Unstructured Demonstrations | 5 |
| 17 | 17 | |
| 18 | 13 | |
| 19 | 10 | |
| 20 | 14 |
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.