Paul Castro
- Computer Networks and Communications top 2%
- Information Systems top 2%
- Electrical and Electronic Engineering
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition top 5%
- Co-authors
- Magdalena BałazińskaVatche IshakianVinod MuthusamyAleksander SlominskiRavi KonuruYu‐Ru LinHari SundaramAisling Kelliher
- Topics
- Service-Oriented Architecture and Web Services (5 papers)Distributed systems and fault tolerance (4 papers)IoT and Edge/Fog Computing (4 papers)
- Journals
- Communications of the ACMIBM Journal of Research and DevelopmentACM Transactions on Knowledge Discovery from Data
- Partner nations
- United StatesSwitzerlandSouth Korea
In The Last Decade
Paul Castro
23 papers receiving 1.0k citations
Hit Papers
Peers
Comparison fields: 5 of 71
- Computer Networks and Communications 782
- Information Systems 369
- Electrical and Electronic Engineering 220
- Artificial Intelligence 200
- Computer Vision and Pattern Recognition 153
Countries citing papers authored by Paul Castro
This map shows the geographic impact of Paul Castro'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 Paul Castro with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Paul Castro more than expected).
Fields of papers citing papers by Paul Castro
This network shows the impact of papers produced by Paul Castro. 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 Paul Castro. The network helps show where Paul Castro may publish in the future.
Co-authorship network of co-authors of Paul Castro
This figure shows the co-authorship network connecting the top 25 collaborators of Paul Castro. A scholar is included among the top collaborators of Paul Castro 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 Paul Castro. Paul Castro 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 | 40 | |
| 3 | 92 | |
| 4 | 1 | |
| 5 | 5 | |
| 6 | 38 | |
| 7 | 29 | |
| 8 | 146 | |
| 9 | 8 | |
| 10 | 2 | |
| 11 | 0 | |
| 12 | 4 | |
| 13 | Mobile Data Management (Part 2) - The Design of a Scalable Discovery Service for Moving Networked Resources. | 2 |
| 14 | 8 | |
| 15 | 30 | |
| 16 | 347 | |
| 17 | 27 | |
| 18 | 3 | |
| 19 | 66 | |
| 20 | 6 |
About Paul Castro
Paul Castro is a scholar working on Computer Networks and Communications, Information Systems and Computer Vision and Pattern Recognition, having authored 25 papers that have together received 1.1k indexed citations. Recurring topics across this work include Service-Oriented Architecture and Web Services (5 papers), Distributed systems and fault tolerance (4 papers) and IoT and Edge/Fog Computing (4 papers). The work is most often cited by research in Computational Mathematics (51 citations), Computer Networks and Communications (782 citations) and Information Systems (369 citations). Paul Castro has collaborated with scholars based in United States, Switzerland and South Korea. Frequent co-authors include Magdalena Bałazińska, Vatche Ishakian, Vinod Muthusamy, Aleksander Slominski, Ravi Konuru, Yu‐Ru Lin, Hari Sundaram, Aisling Kelliher, Jimeng Sun and Perry Cheng. Their work appears in journals such as Communications of the ACM, IBM Journal of Research and Development and ACM Transactions on Knowledge Discovery from Data.
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.