Venkat Chandrasekaran

1.2k citations
27 papers · 589 indexed · h-index 11
Topics
Bayesian Modeling and Causal Inference (7 papers)Advanced Optimization Algorithms Research (7 papers)Sparse and Compressive Sensing Techniques (6 papers)

In The Last Decade

Venkat Chandrasekaran

25 papers receiving 558 citations

Peers

Venkat Chandrasekaran
Comparison fields: 5 of 70
  • Computational Mechanics 214
  • Artificial Intelligence 184
  • Statistics and Probability 121
  • Computational Theory and Mathematics 101
  • Signal Processing 90
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Citations per year

Countries citing papers authored by Venkat Chandrasekaran

Since Specialization
Citations

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

Fields of papers citing papers by Venkat Chandrasekaran

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Venkat Chandrasekaran

This figure shows the co-authorship network connecting the top 25 collaborators of Venkat Chandrasekaran. A scholar is included among the top collaborators of Venkat Chandrasekaran 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 Venkat Chandrasekaran. Venkat Chandrasekaran 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
#WorkIndexed citations
1 1
2 2
3 2
4 16
5 0
6 2
7 5
8
REJOINDER: LATENT VARIABLE GRAPHICAL MODEL SELECTION VIA CONVEX OPTIMIZATION
2
9 48
10 22
11 194
12 0
13 1
14 51
15 21
16 67
17 28
18
Learning Markov Structure by Maximum Entropy Relaxation
9
19
Adaptive Embedded Subgraph Algorithms using Walk-Sum Analysis
1
20
Compression of Higher Dimensional Functions Containing Smooth Discontinuities
5

About Venkat Chandrasekaran

Venkat Chandrasekaran is a scholar working on Numerical Analysis, Statistics and Probability and Computational Theory and Mathematics, having authored 27 papers that have together received 589 indexed citations. Recurring topics across this work include Bayesian Modeling and Causal Inference (7 papers), Advanced Optimization Algorithms Research (7 papers) and Sparse and Compressive Sensing Techniques (6 papers). The work is most often cited by research in Computational Mathematics (19 citations), Numerical Analysis (83 citations) and Statistics and Probability (121 citations). Venkat Chandrasekaran has collaborated with scholars based in United States, Switzerland and Australia. Frequent co-authors include Alan S. Willsky, Pablo A. Parrilo, Parikshit Shah, Sujay Sanghavi, Jason K. Johnson, Adam Wierman, Benjamin Recht, Michael B. Wakin, Richard G. Baraniuk and Animashree Anandkumar. Their work appears in journals such as Proceedings of the National Academy of Sciences, SHILAP Revista de lepidopterología and IEEE Transactions on Information Theory.

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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