Andrew Pannone
- Electrical and Electronic Engineering top 10%
- Materials Chemistry
- Biomedical Engineering
- Cellular and Molecular Neuroscience
- Artificial Intelligence
- Co-authors
- Saptarshi DasShiva Subbulakshmi RadhakrishnanJoan M. RedwingDarsith JayachandranNicholas TrainorMuhtasim Ul Karim SadafNajam U SakibHarikrishnan Ravichandran
- Topics
- Advanced Memory and Neural Computing (11 papers)2D Materials and Applications (6 papers)Ferroelectric and Negative Capacitance Devices (4 papers)
- Partner nations
- United StatesIndiaAustria
In The Last Decade
Andrew Pannone
19 papers receiving 779 citations
Hit Papers
Peers
Comparison fields: 5 of 56
- Electrical and Electronic Engineering 571
- Materials Chemistry 329
- Biomedical Engineering 164
- Cellular and Molecular Neuroscience 123
- Artificial Intelligence 70
Countries citing papers authored by Andrew Pannone
This map shows the geographic impact of Andrew Pannone'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 Andrew Pannone with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andrew Pannone more than expected).
Fields of papers citing papers by Andrew Pannone
This network shows the impact of papers produced by Andrew Pannone. 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 Andrew Pannone. The network helps show where Andrew Pannone may publish in the future.
Co-authorship network of co-authors of Andrew Pannone
This figure shows the co-authorship network connecting the top 25 collaborators of Andrew Pannone. A scholar is included among the top collaborators of Andrew Pannone 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 Andrew Pannone. Andrew Pannone 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 | 4 | |
| 3 | 17 | |
| 4 | 1 | |
| 5 | 2 | |
| 6 | 0 | |
| 7 | Three-dimensional integration of two-dimensional field-effect transistorsbreakdown → | 169 |
| 8 | 3 | |
| 9 | 38 | |
| 10 | 39 | |
| 11 | 13 | |
| 12 | 33 | |
| 13 | 65 | |
| 14 | 10 | |
| 15 | 23 | |
| 16 | 41 | |
| 17 | 157 | |
| 18 | 101 | |
| 19 | 60 | |
| 20 | 12 |
About Andrew Pannone
Andrew Pannone is a scholar working on Biophysics, Hardware and Architecture and Electrical and Electronic Engineering, having authored 20 papers that have together received 789 indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (11 papers), 2D Materials and Applications (6 papers) and Ferroelectric and Negative Capacitance Devices (4 papers). The work is most often cited by research in Hardware and Architecture (68 citations), Electrical and Electronic Engineering (571 citations) and Materials Chemistry (329 citations). Andrew Pannone has collaborated with scholars based in United States, India and Austria. Frequent co-authors include Saptarshi Das, Shiva Subbulakshmi Radhakrishnan, Joan M. Redwing, Darsith Jayachandran, Nicholas Trainor, Muhtasim Ul Karim Sadaf, Najam U Sakib, Harikrishnan Ravichandran, Akhil Dodda and Amritanand Sebastian. Their work appears in journals such as Nature, Nature Communications and Nature Materials.
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.