Gautam Dasarathy

1.3k citations
37 papers · 600 indexed · 1 hit paper · h-index 14
Topics
Machine Learning and Algorithms (9 papers)Sparse and Compressive Sensing Techniques (5 papers)Machine Learning and Data Classification (4 papers)

In The Last Decade

Gautam Dasarathy

36 papers receiving 582 citations

Hit Papers

Digital medicine and the curse of dimensionality2021202620222024202150100150

Peers

Gautam Dasarathy
Comparison fields: 5 of 131
  • Artificial Intelligence 178
  • Electrical and Electronic Engineering 107
  • Cognitive Neuroscience 77
  • Molecular Biology 74
  • Computer Networks and Communications 63
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Citations per field
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Citations per year

Countries citing papers authored by Gautam Dasarathy

Since Specialization
Citations

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

Fields of papers citing papers by Gautam Dasarathy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gautam Dasarathy

This figure shows the co-authorship network connecting the top 25 collaborators of Gautam Dasarathy. A scholar is included among the top collaborators of Gautam Dasarathy 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 Gautam Dasarathy. Gautam Dasarathy 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 4
2 1
3 1
4 51
5 0
6 14
7 6
8
Digital medicine and the curse of dimensionalitybreakdown →
178
9 30
10
Regularization via Structural Label Smoothing
5
11
A Data-Driven and Distributed Approach to Sparse Signal Representation and Recovery
14
12 32
13 1
14
Gaussian Process Bandit Optimisation with Multi-fidelity Evaluations
25
15 2
16
S2: An Efficient Graph Based Active Learning Algorithm with Application to Nonparametric Classification
7
17 3
18 4
19 4
20 28

About Gautam Dasarathy

Gautam Dasarathy is a scholar working on Artificial Intelligence, General Decision Sciences and Signal Processing, having authored 37 papers that have together received 600 indexed citations. Recurring topics across this work include Machine Learning and Algorithms (9 papers), Sparse and Compressive Sensing Techniques (5 papers) and Machine Learning and Data Classification (4 papers). The work is most often cited by research in Health Informatics (21 citations), Computational Mathematics (4 citations) and Human-Computer Interaction (32 citations). Gautam Dasarathy has collaborated with scholars based in United States, Mexico and Israel. Frequent co-authors include Robert D. Nowak, Visar Berisha, Pavan Turaga, P. Richard Hahn, Shira Hahn, Julie Liss, Brian Eriksson, Anamitra Pal, Richard G. Baraniuk and Paul Barford. Their work appears in journals such as IEEE Transactions on Information Theory, IEEE Transactions on Power Systems 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.

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