Kumar Sricharan

1.2k total citations
23 papers, 628 citations indexed

About

Kumar Sricharan is a scholar working on Artificial Intelligence, Computer Networks and Communications and Statistics and Probability. According to data from OpenAlex, Kumar Sricharan has authored 23 papers receiving a total of 628 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Artificial Intelligence, 10 papers in Computer Networks and Communications and 10 papers in Statistics and Probability. Recurrent topics in Kumar Sricharan's work include Statistical Methods and Inference (10 papers), Anomaly Detection Techniques and Applications (7 papers) and Distributed Sensor Networks and Detection Algorithms (5 papers). Kumar Sricharan is often cited by papers focused on Statistical Methods and Inference (10 papers), Anomaly Detection Techniques and Applications (7 papers) and Distributed Sensor Networks and Detection Algorithms (5 papers). Kumar Sricharan collaborates with scholars based in United States, China and France. Kumar Sricharan's co-authors include Alfred O. Hero, Hui Ding, Rama Chellappa, Kamalika Das, Wei Gong, Dawen Yang, Hoshin V. Gupta, Anurag Ganguli, Jonathan Rubin and Ion Matei and has published in prestigious journals such as Water Resources Research, IEEE Transactions on Information Theory and IEEE Transactions on Information Forensics and Security.

In The Last Decade

Kumar Sricharan

23 papers receiving 611 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Kumar Sricharan United States 12 207 156 112 108 81 23 628
George Ostrouchov United States 14 139 0.7× 44 0.3× 57 0.5× 144 1.3× 6 0.1× 55 594
André Gonçalves United States 11 353 1.7× 57 0.4× 103 0.9× 52 0.5× 24 0.3× 32 724
Byungsoo Kim South Korea 15 59 0.3× 287 1.8× 33 0.3× 22 0.2× 9 0.1× 49 652
Ghazanfar Farooq Siddiqui Pakistan 11 143 0.7× 104 0.7× 52 0.5× 44 0.4× 22 0.3× 23 384
Laurie Davies Germany 10 147 0.7× 58 0.4× 56 0.5× 57 0.5× 8 0.1× 26 866
Cullen Schaffer United States 7 390 1.9× 81 0.5× 48 0.4× 27 0.3× 8 0.1× 10 767
Stanley A. Shanies United States 5 342 1.7× 152 1.0× 107 1.0× 17 0.2× 12 0.1× 6 632
Robert E. Banfield United States 8 323 1.6× 104 0.7× 49 0.4× 27 0.3× 7 0.1× 12 514
Suhrid Balakrishnan United States 11 229 1.1× 84 0.5× 199 1.8× 57 0.5× 3 0.0× 18 551
Paweł Karczmarek Poland 13 263 1.3× 147 0.9× 115 1.0× 119 1.1× 3 0.0× 58 564

Countries citing papers authored by Kumar Sricharan

Since Specialization
Citations

This map shows the geographic impact of Kumar Sricharan'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 Kumar Sricharan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kumar Sricharan more than expected).

Fields of papers citing papers by Kumar Sricharan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kumar Sricharan. 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 Kumar Sricharan. The network helps show where Kumar Sricharan may publish in the future.

Co-authorship network of co-authors of Kumar Sricharan

This figure shows the co-authorship network connecting the top 25 collaborators of Kumar Sricharan. A scholar is included among the top collaborators of Kumar Sricharan based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Kumar Sricharan. Kumar Sricharan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Moon, Kevin R., Kumar Sricharan, & Alfred O. Hero. (2021). Ensemble Estimation of Generalized Mutual Information With Applications to Genomics. IEEE Transactions on Information Theory. 67(9). 5963–5996. 5 indexed citations
2.
Sricharan, Kumar, et al.. (2018). Latent Laplacian Maximum Entropy Discrimination for Detection of High-Utility Anomalies. IEEE Transactions on Information Forensics and Security. 13(6). 1446–1459. 11 indexed citations
3.
Moon, Kevin R., Kumar Sricharan, Kristjan Greenewald, & Alfred O. Hero. (2018). Ensemble Estimation of Information Divergence †. Entropy. 20(8). 560–560. 14 indexed citations
4.
Ding, Hui, Kumar Sricharan, & Rama Chellappa. (2018). ExprGAN: Facial Expression Editing With Controllable Expression Intensity. Proceedings of the AAAI Conference on Artificial Intelligence. 32(1). 123 indexed citations
5.
Rubin, Jonathan, Rui Abreu, Anurag Ganguli, et al.. (2016). Classifying Heart Sound Recordings using Deep Convolutional Neural Networks and Mel:Frequency Cepstral Coefficients. Computing in cardiology. 43. 100 indexed citations
6.
Moon, Kevin R., Kumar Sricharan, Kristjan Greenewald, & Alfred O. Hero. (2016). Improving convergence of divergence functional ensemble estimators. 1133–1137. 8 indexed citations
7.
Sricharan, Kumar, et al.. (2015). Detecting Insider Threat from Enterprise Social and Online Activity Data. 13–20. 41 indexed citations
8.
Sricharan, Kumar & Kamalika Das. (2014). Localizing anomalous changes in time-evolving graphs. 1347–1358. 43 indexed citations
9.
Sricharan, Kumar, Dennis Wei, & Alfred O. Hero. (2013). Ensemble Estimators for Multivariate Entropy Estimation. IEEE Transactions on Information Theory. 59(7). 4374–4388. 29 indexed citations
10.
Martin, Rodney, et al.. (2013). Simple Sensitivity Analysis for Orion GNC. AIAA Guidance, Navigation, and Control (GNC) Conference. 4 indexed citations
11.
Eldardiry, Hoda, Kumar Sricharan, Juan Liu, et al.. (2013). Multi-source fusion for anomaly detection: using across-domain and across-time peer-group consistency checks. 5. 39–58. 13 indexed citations
12.
Gong, Wei, Hoshin V. Gupta, Dawen Yang, Kumar Sricharan, & Alfred O. Hero. (2013). Estimating epistemic and aleatory uncertainties during hydrologic modeling: An information theoretic approach. Water Resources Research. 49(4). 2253–2273. 92 indexed citations
13.
Sricharan, Kumar & Alfred O. Hero. (2012). Ensemble weighted kernel estimators for multivariate entropy estimation. Neural Information Processing Systems. 25. 566–574. 3 indexed citations
14.
Sricharan, Kumar & Alfred O. Hero. (2011). Efficient anomaly detection using bipartite k-NN graphs. Neural Information Processing Systems. 24. 478–486. 29 indexed citations
15.
Sricharan, Kumar, Alfred O. Hero, & Bala Rajaratnam. (2011). A local dependence measure and its application to screening for high correlations in large data sets. International Conference on Information Fusion. 1–8. 2 indexed citations
16.
Sricharan, Kumar & Alfred O. Hero. (2011). Weighted k-NN graphs for Rényi entropy estimation in high dimensions. 773–776. 5 indexed citations
17.
Sricharan, Kumar, Raviv Raich, & Alfred O. Hero. (2011). k-nearest neighbor estimation of entropies with confidence. 1205–1209. 5 indexed citations
18.
Sricharan, Kumar, Raviv Raich, & Alfred O. Hero. (2010). Boundary compensated k-NN graphs. 277–282. 4 indexed citations
19.
Sricharan, Kumar, Raviv Raich, & Alfred O. Hero. (2010). Optimized intrinsic dimension estimator using nearest neighbor graphs. 5418–5421. 6 indexed citations
20.
Sricharan, Kumar, Raviv Raich, & Alfred O. Hero. (2009). Global performance prediction for divergence-based image registration criteria. PubMed. 2009. 654–657. 1 indexed citations

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.

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