Federico Corradi
- Electrical and Electronic Engineering top 5%
- Cognitive Neuroscience top 2%
- Cellular and Molecular Neuroscience top 5%
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 5%
- Co-authors
- Giacomo IndiveriNing QiaoHesham MostafaFabio StefaniniMarc OsswaldBojian YinSander M. BohtéTobi Delbrück
- Topics
- Advanced Memory and Neural Computing (41 papers)Neural dynamics and brain function (18 papers)Neural Networks and Reservoir Computing (15 papers)
- Cited by
- Cognitive NeuroscienceCellular and Molecular NeuroscienceElectrical and Electronic Engineering
- Journals
- SensorsIEEE Journal of Solid-State CircuitsIEEE Transactions on Neural Networks and Learning Systems
- Partner nations
- NetherlandsSwitzerlandBelgium
In The Last Decade
Federico Corradi
46 papers receiving 1.7k citations
Hit Papers
Peers
Comparison fields: 5 of 94
- Electrical and Electronic Engineering 1.4k
- Cognitive Neuroscience 678
- Cellular and Molecular Neuroscience 550
- Artificial Intelligence 471
- Computer Vision and Pattern Recognition 233
Countries citing papers authored by Federico Corradi
This map shows the geographic impact of Federico Corradi'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 Federico Corradi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Federico Corradi more than expected).
Fields of papers citing papers by Federico Corradi
This network shows the impact of papers produced by Federico Corradi. 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 Federico Corradi. The network helps show where Federico Corradi may publish in the future.
Co-authorship network of co-authors of Federico Corradi
This figure shows the co-authorship network connecting the top 25 collaborators of Federico Corradi. A scholar is included among the top collaborators of Federico Corradi 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 Federico Corradi. Federico Corradi 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 | 1 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 0 | |
| 6 | 0 | |
| 7 | 0 | |
| 8 | 2 | |
| 9 | 0 | |
| 10 | 1 | |
| 11 | 1 | |
| 12 | 0 | |
| 13 | 38 | |
| 14 | 1 | |
| 15 | 14 | |
| 16 | 205 | |
| 17 | 2 | |
| 18 | 8 | |
| 19 | 12 | |
| 20 | 3 |
About Federico Corradi
Federico Corradi is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Electrical and Electronic Engineering, having authored 56 papers that have together received 1.8k indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (41 papers), Neural dynamics and brain function (18 papers) and Neural Networks and Reservoir Computing (15 papers). The work is most often cited by research in Cognitive Neuroscience (678 citations), Cellular and Molecular Neuroscience (550 citations) and Electrical and Electronic Engineering (1.4k citations). Federico Corradi has collaborated with scholars based in Netherlands, Switzerland and Belgium. Frequent co-authors include Giacomo Indiveri, Ning Qiao, Hesham Mostafa, Fabio Stefanini, Marc Osswald, Bojian Yin, Sander M. Bohté, Tobi Delbrück, Jan Stuijt and Manolis Sifalakis. Their work appears in journals such as Sensors, IEEE Journal of Solid-State Circuits and IEEE Transactions on Neural Networks and Learning Systems.
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.