Sunil Pai
Impact in
- Artificial Intelligence top 2%
- Neural Networks and Reservoir Computing
- Neural Networks and Applications
Papers in ⓘ
-
- Photonic and Optical Devices 12
- Optical Network Technologies 9
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- Neural Networks and Reservoir Computing 10
- Co-authors
- Shanhui Fan (8 shared papers)Ian A. D. Williamson (6 shared papers)Tyler W. Hughes (6 shared papers)Momchil Minkov (6 shared papers)Ben Bartlett (4 shared papers)Olav Solgaard (11 shared papers)David A. B. Miller (6 shared papers)Maziyar Milanizadeh (4 shared papers)
- Journals
- Optica (2 papers)IEEE Journal of Selected Topics in Quantum Electronics (2 papers)Optics Express (1 paper)Scientific Reports (1 paper)Nanophotonics (1 paper)
- Partner nations
- United StatesItalyIndia
In The Last Decade
Sunil Pai
19 papers receiving 603 citations
Hit Papers
Peers
Comparison fields: 5 of 59
- Artificial Intelligence 505
- Acoustics and Ultrasonics 12
- Electrical and Electronic Engineering 514
- Biophysics 17
- Atomic and Molecular Physics, and Optics 65
Countries citing papers authored by Sunil Pai
This map shows the geographic impact of Sunil Pai'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 Sunil Pai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sunil Pai more than expected).
Fields of papers citing papers by Sunil Pai
This network shows the impact of papers produced by Sunil Pai. 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 Sunil Pai. The network helps show where Sunil Pai may publish in the future.
Co-authors
The 25 scholars most cited alongside Sunil Pai, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 223 | |
| 2 | Experimentally realized in situ backpropagation for deep learning in photonic neural networks Hit paper breakdown → | 2023 | 180 |
| 3 | 2020 | 81 | |
| 4 | 2020 | 54 | |
| 5 | 2016 | 25 | |
| 6 | 2017 | 20 | |
| 7 | 2015 | 18 | |
| 8 | 2023 | 17 | |
| 9 | 2011 | 7 | |
| 10 | 2023 | 5 | |
| 11 | 2014 | 4 | |
| 12 | 2024 | 4 | |
| 13 | 2020 | 4 | |
| 14 | 2023 | 4 | |
| 15 | 2015 | 3 | |
| 16 | 2009 | 1 | |
| 17 | 2020 | 1 | |
| 18 | Efficient Visualization Of Streaming Sensor Network Data Using Approximation Technique | 2007 | 1 |
| 19 | 2022 | 1 | |
| 20 | 2024 | 0 |
About Sunil Pai
Sunil Pai is a scholar working on Electrical and Electronic Engineering, Artificial Intelligence, Atomic and Molecular Physics, and Optics, Biomedical Engineering and Organic Chemistry, having authored 20 papers that have together received 653 indexed citations. Recurring topics across this work include Photonic and Optical Devices (12 papers), Neural Networks and Reservoir Computing (10 papers), Optical Network Technologies (9 papers), Advanced Chemical Physics Studies (3 papers), Pluripotent Stem Cells Research (2 papers), CRISPR and Genetic Engineering (2 papers), Acoustic Wave Resonator Technologies (1 paper) and Data Management and Algorithms (1 paper). The work is most often cited by research in Artificial Intelligence (505 citations), Acoustics and Ultrasonics (12 citations), Electrical and Electronic Engineering (514 citations), Biophysics (17 citations) and Atomic and Molecular Physics, and Optics (65 citations). Sunil Pai has collaborated with scholars based in United States, Italy and India. Frequent co-authors include Shanhui Fan, Ian A. D. Williamson, Tyler W. Hughes, Momchil Minkov, Ben Bartlett, Olav Solgaard, David A. B. Miller, Maziyar Milanizadeh, Tae‐Won Park and Andrea Melloni. Their work appears in journals such as Optica, IEEE Journal of Selected Topics in Quantum Electronics, Optics Express, Scientific Reports and Nanophotonics.
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.