Prabhat Prabhat
Impact in
- Hardware and Architecture top 10%
- Parallel Computing and Optimization Techniques
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- Advanced Neural Network Applications
Papers in
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- Stochastic Gradient Optimization Techniques 1
- Computational Physics and Python Applications 1
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- Data Visualization and Analytics 1
- Co-authors
- Diana Moise (1 shared paper)Shirley Ho (1 shared paper)Jason Sewall (1 shared paper)Siyu He (1 shared paper)S. J. Pennycook (1 shared paper)Tuomas Kärnä (1 shared paper)Deborah Bard (1 shared paper)Lei Shao (1 shared paper)
- 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-authors
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 Artificial Intelligence, Computer Vision and Pattern Recognition, Signal Processing, Computational Mechanics and Hardware and Architecture, having authored 4 papers that have together received 131 indexed citations. Recurring topics across this work include Parallel Computing and Optimization Techniques (1 paper), Traffic Prediction and Management Techniques (1 paper), Time Series Analysis and Forecasting (1 paper), Stochastic Gradient Optimization Techniques (1 paper), Computational Physics and Python Applications (1 paper), Data Visualization and Analytics (1 paper), Astrophysics and Cosmic Phenomena (1 paper) and Meteorological Phenomena and Simulations (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 Diana Moise, Shirley Ho, Jason Sewall, Siyu He, S. J. Pennycook, Tuomas Kärnä, Deborah Bard, Lei Shao, Kristyn Maschhoff and Michael F. Ringenburg. 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.