Santosh Kumar Srivastava
- Statistics and Probability top 5%
- Advanced Statistical Methods and Models 6
- Statistical Methods and Inference 5
- Artificial Intelligence top 10%
- Bayesian Methods and Mixture Models 5
- Neural Networks and Applications 2
- Signal Processing top 10%
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- Statistical Mechanics and Entropy 6
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- Network Security and Intrusion Detection 2
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- Network Packet Processing and Optimization 2
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- Big Data and Business Intelligence 1
- Co-authors
- Maya R. GuptaBéla A. FrigyikSergey FeldmanEric GarciaSurbhi BhatiaShivam GuptaAreej MalibariSurajit Bag
- Journals
- IEEE Transactions on Information Theory (1 paper)IEEE Transactions on Knowledge and Data Engineering (1 paper)Journal of Machine Learning Research (1 paper)
- Partner nations
- United StatesIndiaLebanon
In The Last Decade
Santosh Kumar Srivastava
18 papers receiving 392 citations
Peers
Comparison fields: 5 of 109
- Statistics and Probability 74
- Artificial Intelligence 185
- Signal Processing 56
- Statistical and Nonlinear Physics 49
- Computer Vision and Pattern Recognition 68
Countries citing papers authored by Santosh Kumar Srivastava
This map shows the geographic impact of Santosh Kumar Srivastava'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 Santosh Kumar Srivastava with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Santosh Kumar Srivastava more than expected).
Fields of papers citing papers by Santosh Kumar Srivastava
This network shows the impact of papers produced by Santosh Kumar Srivastava. 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 Santosh Kumar Srivastava. The network helps show where Santosh Kumar Srivastava may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Santosh Kumar Srivastava, 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 | 2024 | 17 | |
| 2 | 2023 | 20 | |
| 3 | 2023 | 4 | |
| 4 | Inductive Quantum Embedding | 2020 | 1 |
| 5 | Quantum Embedding of Knowledge for Reasoning | 2019 | 8 |
| 6 | 2019 | 3 | |
| 7 | 2017 | 1 | |
| 8 | Equal Cost Multipath Routing in IP | 2014 | 1 |
| 9 | 2010 | 26 | |
| 10 | Fusing similarities and Euclidean features with generative classifiers | 2009 | 2 |
| 11 | 2009 | 16 | |
| 12 | 2009 | 50 | |
| 13 | 2008 | 18 | |
| 14 | Functional Bregman Divergence and Bayesian Estimation of Distributions (Preprint) | 2008 | 1 |
| 15 | 2008 | 9 | |
| 16 | 2008 | 6 | |
| 17 | 2008 | 58 | |
| 18 | 2007 | 163 | |
| 19 | 2006 | 14 | |
| 20 | 2005 | 0 |
About Santosh Kumar Srivastava
Santosh Kumar Srivastava is a scholar working on Statistics and Probability, Statistical and Nonlinear Physics and Hardware and Architecture, having authored 20 papers that have together received 418 indexed citations. Recurring topics across this work include Advanced Statistical Methods and Models (6 papers), Statistical Mechanics and Entropy (6 papers), Bayesian Methods and Mixture Models (5 papers), Statistical Methods and Inference (5 papers), Network Security and Intrusion Detection (2 papers), Neural Networks and Applications (2 papers), Network Packet Processing and Optimization (2 papers) and Big Data and Business Intelligence (1 paper). The work is most often cited by research in Statistics and Probability (74 citations), Artificial Intelligence (185 citations) and Signal Processing (56 citations). Santosh Kumar Srivastava has collaborated with scholars based in United States, India and Lebanon. Frequent co-authors include Maya R. Gupta, Béla A. Frigyik, Sergey Feldman, Eric Garcia, Surbhi Bhatia, Shivam Gupta, Areej Malibari, Surajit Bag, Paulo Vidal Campregher and H. Joachim Deeg. Their work appears in journals such as IEEE Transactions on Information Theory, IEEE Transactions on Knowledge and Data Engineering and Journal of Machine Learning Research.
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.