Stefano Vassanelli
- Cellular and Molecular Neuroscience top 2%
- Molecular Biology top 10%
- Cognitive Neuroscience top 2%
- Electrical and Electronic Engineering top 10%
- Physiology top 10%
- Co-authors
- Mufti MahmudM. Shamim KaiserAmir HussainMarta MaschiettoPeter FromherzMario ZorattiPaolo BernardiIldikò Szabó
- Topics
- Neuroscience and Neural Engineering (70 papers)Neural dynamics and brain function (55 papers)Advanced Memory and Neural Computing (29 papers)
- Partner nations
- ItalyGermanyUnited Kingdom
In The Last Decade
Stefano Vassanelli
96 papers receiving 2.7k citations
Hit Papers
Peers
Comparison fields: 5 of 163
- Cellular and Molecular Neuroscience 981
- Molecular Biology 815
- Cognitive Neuroscience 771
- Electrical and Electronic Engineering 619
- Physiology 312
Countries citing papers authored by Stefano Vassanelli
This map shows the geographic impact of Stefano Vassanelli'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 Stefano Vassanelli with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stefano Vassanelli more than expected).
Fields of papers citing papers by Stefano Vassanelli
This network shows the impact of papers produced by Stefano Vassanelli. 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 Stefano Vassanelli. The network helps show where Stefano Vassanelli may publish in the future.
Co-authorship network of co-authors of Stefano Vassanelli
This figure shows the co-authorship network connecting the top 25 collaborators of Stefano Vassanelli. A scholar is included among the top collaborators of Stefano Vassanelli 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 Stefano Vassanelli. Stefano Vassanelli 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 | 2 | |
| 3 | 11 | |
| 4 | 31 | |
| 5 | 6 | |
| 6 | 5 | |
| 7 | 33 | |
| 8 | 6 | |
| 9 | Applications of Deep Learning and Reinforcement Learning to Biological Databreakdown → | 544 |
| 10 | 9 | |
| 11 | 3 | |
| 12 | 28 | |
| 13 | 27 | |
| 14 | 24 | |
| 15 | 1 | |
| 16 | 11 | |
| 17 | 55 | |
| 18 | 18 | |
| 19 | 100 | |
| 20 | 280 |
About Stefano Vassanelli
Stefano Vassanelli is a scholar working on Cellular and Molecular Neuroscience, Cognitive Neuroscience and Electrical and Electronic Engineering, having authored 96 papers that have together received 2.8k indexed citations. Recurring topics across this work include Neuroscience and Neural Engineering (70 papers), Neural dynamics and brain function (55 papers) and Advanced Memory and Neural Computing (29 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (981 citations), Cognitive Neuroscience (771 citations) and Biophysics (70 citations). Stefano Vassanelli has collaborated with scholars based in Italy, Germany and United Kingdom. Frequent co-authors include Mufti Mahmud, M. Shamim Kaiser, Amir Hussain, Marta Maschietto, Peter Fromherz, Mario Zoratti, Paolo Bernardi, Ildikò Szabó, Paola Veronese and R. Colonna. Their work appears in journals such as Advanced Materials, Journal of Biological Chemistry and Nature Communications.
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.