Stefano Vassanelli

3.9k citations
96 papers · 2.8k indexed · 1 hit paper · h-index 25

Stefano Vassanelli

96 papers receiving 2.7k citations

Hit Papers

Applications of Deep Learning and Reinforcement Learning ...5442018202620202023100200300400500

Peers

Stefano Vassanelli
Comparison fields: 5 of 163
  • Cellular and Molecular Neuroscience 981
  • Cognitive Neuroscience 771
  • Biophysics 70
  • Physiology 312
  • Health Informatics 16
Replace Henggui Zhang with:
Henggui Zhang United Kingdom
Kyung Hwan Kim South Korea
Ghanim Ullah United States
Hang Hu United States
Hitten P. Zaveri United States
Benjamin H. Brinkmann United States
Jochen Klucken Germany
Xiaoxiang Zheng China
Hua Han China
Stefano Vassanelli relative to Henggui Zhang United Kingdom Henggui Zhang's profile →
Citations per field
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Citations per year

Countries citing papers authored by Stefano Vassanelli

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

The 25 scholars most cited alongside Stefano Vassanelli, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Stefano Vassanelli Line = papers co-authored together Stefano Vassanelli links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20251
2 20232
3 202111
4 202131
5 20216
6 20205
7 202033
8 20206
9
Applications of Deep Learning and Reinforcement Learning to Biological Databreakdown →
2018544
10 20189
11 20173
12 201628
13 201627
14 201424
15 20111
16 201011
17 200755
18 200618
19 2001100
20 1996280

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), Advanced Memory and Neural Computing (29 papers), EEG and Brain-Computer Interfaces (29 papers), Neuroscience and Neuropharmacology Research (11 papers), Ion channel regulation and function (10 papers), Photoreceptor and optogenetics research (9 papers) and Functional Brain Connectivity Studies (5 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.

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