Paolo Costa
About
In The Last Decade
Paolo Costa
103 papers receiving 3.5k citations
Hit Papers
Peers
Comparison fields: 5 of 78
- Computer Networks and Communications 3.0k
- Information Systems 1.8k
- Electrical and Electronic Engineering 775
- Artificial Intelligence 446
- Computer Vision and Pattern Recognition 359
Countries citing papers authored by Paolo Costa
This map shows the geographic impact of Paolo Costa'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 Paolo Costa with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Paolo Costa more than expected).
Fields of papers citing papers by Paolo Costa
This network shows the impact of papers produced by Paolo Costa. 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 Paolo Costa. The network helps show where Paolo Costa may publish in the future.
Co-authorship network of co-authors of Paolo Costa
This figure shows the co-authorship network connecting the top 25 collaborators of Paolo Costa. A scholar is included among the top collaborators of Paolo Costa 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 Paolo Costa. Paolo Costa 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 | In-network Aggregation for Shared Machine Learning Clusters | 29 |
| 3 | Shoal: A Network Architecture for Disaggregated Racks | 26 |
| 4 | Beyond SmartNICs: Towards a Fully Programmable Cloud | 12 |
| 5 | 18 | |
| 6 | 81 | |
| 7 | Optimizing network performance in distributed machine learning | 25 |
| 8 | 46 | |
| 9 | Rethinking the network stack for rack-scale computers | 11 |
| 10 | Exploiting Time-Malleability in Cloud-based Batch Processing Systems | 5 |
| 11 | Camdoop: exploiting in-network aggregation for big data applications | 115 |
| 12 | NaaS: network-as-a-service in the cloud | 62 |
| 13 | The LighTS tuple space framework and its customization for context-aware applications | 18 |
| 14 | 59 | |
| 15 | Towards Conceptual Foundations for Context-Aware Applications | 8 |
| 16 | Charles Taylor, Modern Social Imaginaries | 1 |
| 17 | Using ontologies for modeling context-aware services platforms | 6 |
| 18 | 29 | |
| 19 | 25 | |
| 20 | 12 |
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.