S. Sandilya
Impact in
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- Statistical Methods and Inference
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- Face and Expression Recognition
- Image and Signal Denoising Methods
- Image Retrieval and Classification Techniques
Papers in
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- Particle physics theoretical and experimental studies 4
- Quantum Chromodynamics and Particle Interactions 3
- Particle Detector Development and Performance 3
- High-Energy Particle Collisions Research 2
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- Radiation Detection and Scintillator Technologies 3
- Co-authors
- Sanjeev R. Kulkarni (3 shared papers)Steven E. Posner (2 shared papers)Taikan Suehara (1 shared paper)Takashi Yamanaka (1 shared paper)Deepak Samuel (1 shared paper)S. Kohani (1 shared paper)T. Mibe (1 shared paper)T. E. Browder (1 shared paper)
- Journals
- IEEE Transactions on Information Theory (2 papers)Journal of High Energy Physics (1 paper)Journal of Physics Conference Series (2 papers)Proceedings Of Science (1 paper)
- Partner nations
- United StatesIndiaItaly
In The Last Decade
S. Sandilya
7 papers receiving 46 citations
Peers
Comparison fields: 5 of 29
- Statistics and Probability 8
- Computer Vision and Pattern Recognition 19
- Signal Processing 8
- Artificial Intelligence 20
- Computer Graphics and Computer-Aided Design 2
Countries citing papers authored by S. Sandilya
This map shows the geographic impact of S. Sandilya'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 S. Sandilya with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites S. Sandilya more than expected).
Fields of papers citing papers by S. Sandilya
This network shows the impact of papers produced by S. Sandilya. 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 S. Sandilya. The network helps show where S. Sandilya may publish in the future.
Co-authors
The 15 scholars most cited alongside S. Sandilya, 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 | 2002 | 34 | |
| 2 | 2002 | 9 | |
| 3 | 2017 | 3 | |
| 4 | 2022 | 1 | |
| 5 | 2016 | 1 | |
| 6 | 2024 | 1 | |
| 7 | 2002 | 1 | |
| 8 | 2018 | 1 | |
| 9 | 2024 | 0 |
About S. Sandilya
S. Sandilya is a scholar working on Nuclear and High Energy Physics, Radiation, Artificial Intelligence, Statistics and Probability and Computer Vision and Pattern Recognition, having authored 9 papers that have together received 51 indexed citations. Recurring topics across this work include Particle physics theoretical and experimental studies (4 papers), Quantum Chromodynamics and Particle Interactions (3 papers), Radiation Detection and Scintillator Technologies (3 papers), Particle Detector Development and Performance (3 papers), Markov Chains and Monte Carlo Methods (2 papers), High-Energy Particle Collisions Research (2 papers), Statistical Methods and Inference (2 papers) and Superconducting Materials and Applications (1 paper). The work is most often cited by research in Statistics and Probability (8 citations), Computer Vision and Pattern Recognition (19 citations), Signal Processing (8 citations), Artificial Intelligence (20 citations) and Computer Graphics and Computer-Aided Design (2 citations). S. Sandilya has collaborated with scholars based in United States, India and Italy. Frequent co-authors include Sanjeev R. Kulkarni, Steven E. Posner, Taikan Suehara, Takashi Yamanaka, Deepak Samuel, S. Kohani, T. Mibe, T. E. Browder, S. Dubey and A. J. Schwartz. Their work appears in journals such as IEEE Transactions on Information Theory, Journal of High Energy Physics, Journal of Physics Conference Series and Proceedings Of Science.
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.