Prabhat Prabhat
- Hardware and Architecture top 10%
- Parallel Computing and Optimization Techniques 1
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- Advanced Neural Network Applications 1
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- Astrophysics and Cosmic Phenomena 1
- Neutrino Physics Research 1
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- Time Series Analysis and Forecasting 1
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- Sparse and Compressive Sensing Techniques 1
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- Stochastic Gradient Optimization Techniques 1
- Computational Physics and Python Applications 1
- Co-authors
- Tuomas KärnäKristyn MaschhoffShirley HoLei ShaoDeborah BardSiyu HeVictor C. S. LeeDiana Moise
- Journals
- arXiv (Cornell University) (1 paper)Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE (1 paper)OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (1 paper)
- Partner nations
- United StatesSwitzerlandUnited Kingdom
In The Last Decade
Prabhat Prabhat
3 papers receiving 129 citations
Peers
Comparison fields: 5 of 40
- Hardware and Architecture 35
- Computer Vision and Pattern Recognition 51
- Computational Mathematics 1
- Computer Networks and Communications 36
- Nuclear and High Energy Physics 19
Countries citing papers authored by Prabhat Prabhat
This map shows the geographic impact of Prabhat Prabhat'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 Prabhat Prabhat with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Prabhat Prabhat more than expected).
Fields of papers citing papers by Prabhat Prabhat
This network shows the impact of papers produced by Prabhat Prabhat. 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 Prabhat Prabhat. The network helps show where Prabhat Prabhat may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Prabhat Prabhat, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
About Prabhat Prabhat
Prabhat Prabhat is a scholar working on Hardware and Architecture, Computer Vision and Pattern Recognition, Artificial Intelligence, Signal Processing and Nuclear and High Energy Physics, having authored 4 papers that have together received 131 indexed citations. Recurring topics across this work include Time Series Analysis and Forecasting (1 paper), Sparse and Compressive Sensing Techniques (1 paper), Stochastic Gradient Optimization Techniques (1 paper), Astrophysics and Cosmic Phenomena (1 paper), Computational Physics and Python Applications (1 paper), Parallel Computing and Optimization Techniques (1 paper), Advanced Neural Network Applications (1 paper) and Neutrino Physics Research (1 paper). The work is most often cited by research in Hardware and Architecture (35 citations), Computer Vision and Pattern Recognition (51 citations), Computational Mathematics (1 citation), Computer Networks and Communications (36 citations) and Nuclear and High Energy Physics (19 citations). Prabhat Prabhat has collaborated with scholars based in United States, Switzerland and United Kingdom. Frequent co-authors include Tuomas Kärnä, Kristyn Maschhoff, Shirley Ho, Lei Shao, Deborah Bard, Siyu He, Victor C. S. Lee, Diana Moise, Jason Sewall and S. J. Pennycook. Their work appears in journals such as arXiv (Cornell University), Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE and OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information).
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.