Alvaro Velasquez
- Neurology top 10%
- Electrical and Electronic Engineering
- Artificial Intelligence top 10%
- Infectious Diseases
- Biomedical Engineering
- Co-authors
- Sumit Kumar JhaSusmit JhaSara C. AuldKarima BenameurRaymond F. SchinaziWilliam T. HuMark E. MullinsTuğba Öztürk
- Topics
- Reinforcement Learning in Robotics (13 papers)Advanced Memory and Neural Computing (12 papers)Adversarial Robustness in Machine Learning (11 papers)
- Cited by
- NeurologyInfectious Diseases
- Journals
- SHILAP Revista de lepidopterologíaBioinformaticsAmerican Journal of Respiratory and Critical Care Medicine
- Partner nations
- United StatesColombiaMexico
In The Last Decade
Alvaro Velasquez
81 papers receiving 741 citations
Peers
Comparison fields: 5 of 131
- Neurology 136
- Electrical and Electronic Engineering 131
- Artificial Intelligence 127
- Infectious Diseases 95
- Biomedical Engineering 84
Countries citing papers authored by Alvaro Velasquez
This map shows the geographic impact of Alvaro Velasquez'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 Alvaro Velasquez with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Alvaro Velasquez more than expected).
Fields of papers citing papers by Alvaro Velasquez
This network shows the impact of papers produced by Alvaro Velasquez. 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 Alvaro Velasquez. The network helps show where Alvaro Velasquez may publish in the future.
Co-authorship network of co-authors of Alvaro Velasquez
This figure shows the co-authorship network connecting the top 25 collaborators of Alvaro Velasquez. A scholar is included among the top collaborators of Alvaro Velasquez 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 Alvaro Velasquez. Alvaro Velasquez 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 | 3 | |
| 4 | 1 | |
| 5 | 12 | |
| 6 | 2 | |
| 7 | 4 | |
| 8 | 6 | |
| 9 | 1 | |
| 10 | 0 | |
| 11 | 1 | |
| 12 | 0 | |
| 13 | 1 | |
| 14 | 18 | |
| 15 | 1 | |
| 16 | 15 | |
| 17 | On the Susceptibility of Deep Neural Networks to Natural Perturbations. | 2 |
| 18 | 6 | |
| 19 | Caracterización de Imanes para aplicación en sistemas de sensado de posición | 0 |
| 20 | 60 |
About Alvaro Velasquez
Alvaro Velasquez is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Renewable Energy, Sustainability and the Environment, having authored 94 papers that have together received 760 indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (13 papers), Advanced Memory and Neural Computing (12 papers) and Adversarial Robustness in Machine Learning (11 papers). The work is most often cited by research in Neurology (136 citations), Infectious Diseases (95 citations) and Neurology (41 citations). Alvaro Velasquez has collaborated with scholars based in United States, Colombia and Mexico. Frequent co-authors include Sumit Kumar Jha, Susmit Jha, Sara C. Auld, Karima Benameur, Raymond F. Schinazi, William T. Hu, Mark E. Mullins, Tuğba Öztürk, Houbing Song and J. Christina Howell. Their work appears in journals such as SHILAP Revista de lepidopterología, Bioinformatics and American Journal of Respiratory and Critical Care Medicine.
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.