Ameya Velingker
- Computational Mechanics
- Artificial Intelligence
- Computer Networks and Communications
- Computational Theory and Mathematics
- Electrical and Electronic Engineering
- Co-authors
- Venkatesan GuruswamiMahdi CheraghchiMichael KapralovCameron MuscoChristopher MuscoMadhu SudanHaim AvronSanjeev Khanna
- Topics
- Complexity and Algorithms in Graphs (6 papers)Sparse and Compressive Sensing Techniques (3 papers)Cryptography and Data Security (3 papers)
- Journals
- Linear Algebra and its ApplicationsSymposium on Discrete AlgorithmsInternational Conference on Machine Learning
- Partner nations
- United StatesDenmarkSwitzerland
In The Last Decade
Ameya Velingker
11 papers receiving 81 citations
Peers
Comparison fields: 5 of 34
- Computational Mechanics 31
- Artificial Intelligence 31
- Computer Networks and Communications 29
- Computational Theory and Mathematics 29
- Electrical and Electronic Engineering 16
Countries citing papers authored by Ameya Velingker
This map shows the geographic impact of Ameya Velingker'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 Ameya Velingker with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ameya Velingker more than expected).
Fields of papers citing papers by Ameya Velingker
This network shows the impact of papers produced by Ameya Velingker. 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 Ameya Velingker. The network helps show where Ameya Velingker may publish in the future.
Co-authorship network of co-authors of Ameya Velingker
This figure shows the co-authorship network connecting the top 25 collaborators of Ameya Velingker. A scholar is included among the top collaborators of Ameya Velingker 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 Ameya Velingker. Ameya Velingker is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 7 | |
| 2 | 1 | |
| 3 | 2 | |
| 4 | 1 | |
| 5 | Random Fourier Features for Kernel Ridge Regression: Approximation Bounds and Statistical Guarantees | 15 |
| 6 | 6 | |
| 7 | 7 | |
| 8 | 6 | |
| 9 | Constructing Ramanujan Graphs Using Shift Lifts. | 1 |
| 10 | 0 | |
| 11 | 12 | |
| 12 | Restricted Isometry of Fourier Matrices and List Decodability of Random Linear Codes | 26 |
About Ameya Velingker
Ameya Velingker is a scholar working on Computational Theory and Mathematics, Discrete Mathematics and Combinatorics and Geometry and Topology, having authored 12 papers that have together received 84 indexed citations. Recurring topics across this work include Complexity and Algorithms in Graphs (6 papers), Sparse and Compressive Sensing Techniques (3 papers) and Cryptography and Data Security (3 papers). The work is most often cited by research in Computational Theory and Mathematics (29 citations), Computational Mathematics (1 citation) and Computational Mechanics (31 citations). Ameya Velingker has collaborated with scholars based in United States, Denmark and Switzerland. Frequent co-authors include Venkatesan Guruswami, Mahdi Cheraghchi, Michael Kapralov, Cameron Musco, Christopher Musco, Madhu Sudan, Haim Avron, Sanjeev Khanna, Bernhard Haeupler and Pritish Kamath. Their work appears in journals such as Linear Algebra and its Applications, Symposium on Discrete Algorithms and International Conference on Machine Learning.
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.