Luca Pancioni
- Computer Networks and Communications top 2%
- Electrical and Electronic Engineering top 10%
- Statistical and Nonlinear Physics top 2%
- Artificial Intelligence top 5%
- Control and Systems Engineering top 10%
- Co-authors
- Mauro FortiMauro Di MarcoMassimiliano GrazziniPaolo NistriValerio VignoliS. RocchiMassimo AliotoA. Tesi
- Topics
- Neural Networks Stability and Synchronization (38 papers)Advanced Memory and Neural Computing (30 papers)stochastic dynamics and bifurcation (28 papers)
- Cited by
- Statistical and Nonlinear PhysicsComputer Networks and CommunicationsElectrical and Electronic Engineering
In The Last Decade
Luca Pancioni
54 papers receiving 992 citations
Peers
Comparison fields: 5 of 47
- Computer Networks and Communications 666
- Electrical and Electronic Engineering 555
- Statistical and Nonlinear Physics 431
- Artificial Intelligence 272
- Control and Systems Engineering 91
Countries citing papers authored by Luca Pancioni
This map shows the geographic impact of Luca Pancioni'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 Luca Pancioni with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Luca Pancioni more than expected).
Fields of papers citing papers by Luca Pancioni
This network shows the impact of papers produced by Luca Pancioni. 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 Luca Pancioni. The network helps show where Luca Pancioni may publish in the future.
Co-authorship network of co-authors of Luca Pancioni
This figure shows the co-authorship network connecting the top 25 collaborators of Luca Pancioni. A scholar is included among the top collaborators of Luca Pancioni 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 Luca Pancioni. Luca Pancioni is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 0 | |
| 3 | 8 | |
| 4 | 1 | |
| 5 | 1 | |
| 6 | 11 | |
| 7 | 2 | |
| 8 | 24 | |
| 9 | 47 | |
| 10 | 2 | |
| 11 | 1 | |
| 12 | 14 | |
| 13 | 28 | |
| 14 | 17 | |
| 15 | 4 | |
| 16 | 2 | |
| 17 | 1 | |
| 18 | 2 | |
| 19 | 14 | |
| 20 | 14 |
About Luca Pancioni
Luca Pancioni is a scholar working on Statistical and Nonlinear Physics, Computer Networks and Communications and Electrical and Electronic Engineering, having authored 56 papers that have together received 1.0k indexed citations. Recurring topics across this work include Neural Networks Stability and Synchronization (38 papers), Advanced Memory and Neural Computing (30 papers) and stochastic dynamics and bifurcation (28 papers). The work is most often cited by research in Statistical and Nonlinear Physics (431 citations), Computer Networks and Communications (666 citations) and Electrical and Electronic Engineering (555 citations). Luca Pancioni has collaborated with scholars based in Italy and Hungary. Frequent co-authors include Mauro Forti, Mauro Di Marco, Massimiliano Grazzini, Paolo Nistri, Valerio Vignoli, S. Rocchi, Massimo Alioto, A. Tesi, Ada Fort and Giacomo Innocenti. Their work appears in journals such as IEEE Access, IEEE Transactions on Cybernetics 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.