Ankur Moitra
Impact in
- Computational Mathematics top 1%
- Tensor decomposition and applications
- Signal Processing top 5%
- Blind Source Separation Techniques
Papers in
-
- Machine Learning and Algorithms 14
- Algorithms and Data Compression 8
-
- Complexity and Algorithms in Graphs 13
- Advanced Graph Theory Research 7
- Matrix Theory and Algorithms 6
- Co-authors
- Sanjeev Arora (6 shared papers)Gregory Valiant (3 shared papers)Rong Ge (2 shared papers)Rong Ge (4 shared papers)Adam Tauman Kalai (3 shared papers)Tom Leighton (3 shared papers)Ravindran Kannan (1 shared paper)Ran Gelles (2 shared papers)
- Journals
- SIAM Journal on Computing (4 papers)Communications of the ACM (3 papers)Journal of the ACM (2 papers)Algorithmica (1 paper)Discrete & Computational Geometry (1 paper)
- Partner nations
- United StatesCanadaIsrael
In The Last Decade
Ankur Moitra
59 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 110
- Computational Mathematics 96
- Signal Processing 185
- Artificial Intelligence 537
- Computational Theory and Mathematics 265
- Computer Graphics and Computer-Aided Design 54
Countries citing papers authored by Ankur Moitra
This map shows the geographic impact of Ankur Moitra'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 Ankur Moitra with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ankur Moitra more than expected).
Fields of papers citing papers by Ankur Moitra
This network shows the impact of papers produced by Ankur Moitra. 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 Ankur Moitra. The network helps show where Ankur Moitra may publish in the future.
Co-authors
The 25 scholars most cited alongside Ankur Moitra, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 63 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2012 | 168 | |
| 2 | 2012 | 144 | |
| 3 | 2010 | 109 | |
| 4 | 2010 | 78 | |
| 5 | 2015 | 66 | |
| 6 | 2014 | 41 | |
| 7 | 2011 | 41 | |
| 8 | 2013 | 36 | |
| 9 | 2009 | 34 | |
| 10 | 2018 | 34 | |
| 11 | 2008 | 33 | |
| 12 | 2014 | 30 | |
| 13 | 2011 | 27 | |
| 14 | 2009 | 26 | |
| 15 | 2016 | 22 | |
| 16 | 2012 | 22 | |
| 17 | 2010 | 21 | |
| 18 | 2013 | 17 | |
| 19 | 2012 | 16 | |
| 20 | 2015 | 15 |
About Ankur Moitra
Ankur Moitra is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Computer Networks and Communications, Computational Mechanics and Statistics and Probability, having authored 63 papers that have together received 1.2k indexed citations. Recurring topics across this work include Machine Learning and Algorithms (14 papers), Complexity and Algorithms in Graphs (13 papers), Sparse and Compressive Sensing Techniques (9 papers), Algorithms and Data Compression (8 papers), Advanced Graph Theory Research (7 papers), Tensor decomposition and applications (7 papers), Optimization and Search Problems (6 papers) and Matrix Theory and Algorithms (6 papers). The work is most often cited by research in Computational Mathematics (96 citations), Signal Processing (185 citations), Artificial Intelligence (537 citations), Computational Theory and Mathematics (265 citations) and Computer Graphics and Computer-Aided Design (54 citations). Ankur Moitra has collaborated with scholars based in United States, Canada and Israel. Frequent co-authors include Sanjeev Arora, Gregory Valiant, Rong Ge, Rong Ge, Adam Tauman Kalai, Tom Leighton, Ravindran Kannan, Ran Gelles, Amit Sahai and Mark Braverman. Their work appears in journals such as SIAM Journal on Computing, Communications of the ACM, Journal of the ACM, Algorithmica and Discrete & Computational Geometry.
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.