Miguel A. Padilla
- Mechanical Engineering top 10%
- Social Psychology top 10%
- Clinical Psychology top 10%
- Sociology and Political Science
- Statistics and Probability top 5%
- Co-authors
- Jasmin DiversJocelyn BonjourRémi RevellinRobert J. MilletichRobin J. LewisDavid B. AllisonCathy Lau‐BarracoMichelle L. Kelley
- Topics
- Statistical Methods and Bayesian Inference (8 papers)Advanced Statistical Methods and Models (8 papers)Heat Transfer and Optimization (5 papers)
- Partner nations
- United StatesGhanaFrance
In The Last Decade
Miguel A. Padilla
35 papers receiving 761 citations
Peers
Comparison fields: 5 of 134
- Mechanical Engineering 167
- Social Psychology 139
- Clinical Psychology 123
- Sociology and Political Science 101
- Statistics and Probability 78
Countries citing papers authored by Miguel A. Padilla
This map shows the geographic impact of Miguel A. Padilla'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 Miguel A. Padilla with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Miguel A. Padilla more than expected).
Fields of papers citing papers by Miguel A. Padilla
This network shows the impact of papers produced by Miguel A. Padilla. 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 Miguel A. Padilla. The network helps show where Miguel A. Padilla may publish in the future.
Co-authorship network of co-authors of Miguel A. Padilla
This figure shows the co-authorship network connecting the top 25 collaborators of Miguel A. Padilla. A scholar is included among the top collaborators of Miguel A. Padilla 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 Miguel A. Padilla. Miguel A. Padilla is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 1 | |
| 3 | 0 | |
| 4 | 2 | |
| 5 | 42 | |
| 6 | 34 | |
| 7 | 45 | |
| 8 | 16 | |
| 9 | 35 | |
| 10 | 5 | |
| 11 | 8 | |
| 12 | Light-Exoskeleton and Data-Glove integration for enhancing virtual reality applications | 3 |
| 13 | 26 | |
| 14 | 8 | |
| 15 | 131 | |
| 16 | 2 | |
| 17 | 12 | |
| 18 | 19 | |
| 19 | 11 | |
| 20 | 3 |
About Miguel A. Padilla
Miguel A. Padilla is a scholar working on Statistics and Probability, Architecture and Management Science and Operations Research, having authored 38 papers that have together received 803 indexed citations. Recurring topics across this work include Statistical Methods and Bayesian Inference (8 papers), Advanced Statistical Methods and Models (8 papers) and Heat Transfer and Optimization (5 papers). The work is most often cited by research in Statistics and Probability (78 citations), Health (75 citations) and Applied Psychology (43 citations). Miguel A. Padilla has collaborated with scholars based in United States, Ghana and France. Frequent co-authors include Jasmin Divers, Jocelyn Bonjour, Rémi Revellin, Robert J. Milletich, Robin J. Lewis, David B. Allison, Cathy Lau‐Barraco, Michelle L. Kelley, Jasmin Divers and James Algina. Their work appears in journals such as PLoS ONE, Genetics and Energy Conversion and Management.
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.