Massimo A. Sivilotti
- Electrical and Electronic Engineering
- Artificial Intelligence top 10%
- Biomedical Engineering
- Computer Networks and Communications
- Cognitive Neuroscience
- Co-authors
- Carver MeadDouglas KernsJin LuoMartin FiersWim BogaertsPieter DumonMisha MahowaldJohn Wawrzynek
- Topics
- Advanced Memory and Neural Computing (5 papers)Neural Networks and Applications (4 papers)Neural dynamics and brain function (3 papers)
- Journals
- IEEE Transactions on Neural NetworksCaltechAUTHORS (California Institute of Technology)Optical Fiber Communication Conference
- Partner nations
- United States
In The Last Decade
Massimo A. Sivilotti
8 papers receiving 215 citations
Peers
Comparison fields: 5 of 31
- Electrical and Electronic Engineering 169
- Artificial Intelligence 143
- Biomedical Engineering 36
- Computer Networks and Communications 24
- Cognitive Neuroscience 23
Countries citing papers authored by Massimo A. Sivilotti
This map shows the geographic impact of Massimo A. Sivilotti'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 Massimo A. Sivilotti with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Massimo A. Sivilotti more than expected).
Fields of papers citing papers by Massimo A. Sivilotti
This network shows the impact of papers produced by Massimo A. Sivilotti. 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 Massimo A. Sivilotti. The network helps show where Massimo A. Sivilotti may publish in the future.
Co-authorship network of co-authors of Massimo A. Sivilotti
This figure shows the co-authorship network connecting the top 25 collaborators of Massimo A. Sivilotti. A scholar is included among the top collaborators of Massimo A. Sivilotti 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 Massimo A. Sivilotti. Massimo A. Sivilotti is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 9 | |
| 2 | 6 | |
| 3 | CMOS UV-writable non-volatile analog storage | 23 |
| 4 | 3 | |
| 5 | A novel associative memory implemented using collective computation | 26 |
| 6 | 58 | |
| 7 | Real-time visual computations using analog CMOS processing arrays | 87 |
| 8 | 20 |
About Massimo A. Sivilotti
Massimo A. Sivilotti is a scholar working on Artificial Intelligence, Cognitive Neuroscience and Electrical and Electronic Engineering, having authored 8 papers that have together received 232 indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (5 papers), Neural Networks and Applications (4 papers) and Neural dynamics and brain function (3 papers). The work is most often cited by research in Artificial Intelligence (143 citations), Electrical and Electronic Engineering (169 citations) and Media Technology (12 citations). Massimo A. Sivilotti has collaborated with scholars based in United States. Frequent co-authors include Carver Mead, Douglas Kerns, Jin Luo, Martin Fiers, Wim Bogaerts, Pieter Dumon, Misha Mahowald, John Wawrzynek and John Lazzaro. Their work appears in journals such as IEEE Transactions on Neural Networks, CaltechAUTHORS (California Institute of Technology) and Optical Fiber Communication Conference.
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.