Advait Madhavan
- Electrical and Electronic Engineering top 10%
- Artificial Intelligence top 10%
- Atomic and Molecular Physics, and Optics
- Cellular and Molecular Neuroscience
- Computer Networks and Communications
- Co-authors
- Dmitri B. StrukovTimothy SherwoodM. D. StilesMatthew W. DanielsPhilippe TalatchianBrian D. HoskinsLuke TheogarajanMiguel Ángel Lastras-Montaño
- Topics
- Advanced Memory and Neural Computing (27 papers)Ferroelectric and Negative Capacitance Devices (12 papers)Neuroscience and Neural Engineering (7 papers)
- Partner nations
- United StatesFranceJapan
In The Last Decade
Advait Madhavan
34 papers receiving 471 citations
Peers
Comparison fields: 5 of 34
- Electrical and Electronic Engineering 383
- Artificial Intelligence 144
- Atomic and Molecular Physics, and Optics 85
- Cellular and Molecular Neuroscience 73
- Computer Networks and Communications 50
Countries citing papers authored by Advait Madhavan
This map shows the geographic impact of Advait Madhavan'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 Advait Madhavan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Advait Madhavan more than expected).
Fields of papers citing papers by Advait Madhavan
This network shows the impact of papers produced by Advait Madhavan. 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 Advait Madhavan. The network helps show where Advait Madhavan may publish in the future.
Co-authorship network of co-authors of Advait Madhavan
This figure shows the co-authorship network connecting the top 25 collaborators of Advait Madhavan. A scholar is included among the top collaborators of Advait Madhavan 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 Advait Madhavan. Advait Madhavan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 0 | |
| 5 | 10 | |
| 6 | 9 | |
| 7 | 15 | |
| 8 | 15 | |
| 9 | 8 | |
| 10 | 6 | |
| 11 | 2 | |
| 12 | 52 | |
| 13 | A Truth-Matrix View into Unary Computing | 1 |
| 14 | 9 | |
| 15 | 16 | |
| 16 | 44 | |
| 17 | 11 | |
| 18 | 42 | |
| 19 | 5 | |
| 20 | 5 |
About Advait Madhavan
Advait Madhavan is a scholar working on Electrical and Electronic Engineering, Artificial Intelligence and Cellular and Molecular Neuroscience, having authored 37 papers that have together received 483 indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (27 papers), Ferroelectric and Negative Capacitance Devices (12 papers) and Neuroscience and Neural Engineering (7 papers). The work is most often cited by research in Electrical and Electronic Engineering (383 citations), Hardware and Architecture (38 citations) and Artificial Intelligence (144 citations). Advait Madhavan has collaborated with scholars based in United States, France and Japan. Frequent co-authors include Dmitri B. Strukov, Timothy Sherwood, M. D. Stiles, Matthew W. Daniels, Philippe Talatchian, Brian D. Hoskins, Luke Theogarajan, Miguel Ángel Lastras-Montaño, Kwang‐Ting Cheng and Melika Payvand. Their work appears in journals such as Nature Communications, Applied Physics Letters and Scientific Reports.
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.