David P. Woodruff
- Artificial Intelligence top 0.5%
- Computational Mechanics top 1%
- Computational Theory and Mathematics top 0.5%
- Computer Networks and Communications top 2%
- Computer Vision and Pattern Recognition top 2%
- Co-authors
- Kenneth L. ClarksonPiotr IndykJelani NelsonDaniel M. KanePetros DrineasChristos BoutsidisEric PriceMichael W. Mahoney
- Topics
- Complexity and Algorithms in Graphs (73 papers)Sparse and Compressive Sensing Techniques (69 papers)Stochastic Gradient Optimization Techniques (64 papers)
- Partner nations
- United StatesChinaIsrael
In The Last Decade
David P. Woodruff
174 papers receiving 2.9k citations
Hit Papers
Peers
Comparison fields: 5 of 97
- Artificial Intelligence 1.9k
- Computational Mechanics 1.0k
- Computational Theory and Mathematics 1.0k
- Computer Networks and Communications 758
- Computer Vision and Pattern Recognition 531
Countries citing papers authored by David P. Woodruff
This map shows the geographic impact of David P. Woodruff'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 David P. Woodruff with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David P. Woodruff more than expected).
Fields of papers citing papers by David P. Woodruff
This network shows the impact of papers produced by David P. Woodruff. 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 David P. Woodruff. The network helps show where David P. Woodruff may publish in the future.
Co-authorship network of co-authors of David P. Woodruff
This figure shows the co-authorship network connecting the top 25 collaborators of David P. Woodruff. A scholar is included among the top collaborators of David P. Woodruff 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 David P. Woodruff. David P. Woodruff is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 2 | |
| 3 | 4 | |
| 4 | 1 | |
| 5 | A Very Sketchy Talk (Invited Talk). | 1 |
| 6 | Learning-Augmented Data Stream Algorithms | 4 |
| 7 | 1 | |
| 8 | 3 | |
| 9 | Efficient and Thrifty Voting by Any Means Necessary | 11 |
| 10 | 5 | |
| 11 | 0 | |
| 12 | Leveraging Well-Conditioned Bases: Streaming and Distributed Summaries in Minkowski $p$-Norms | 1 |
| 13 | Is Input Sparsity Time Possible for Kernel Low-Rank Approximation? | 1 |
| 14 | 9 | |
| 15 | Sublinear time orthogonal tensor decomposition | 10 |
| 16 | 17 | |
| 17 | Distributed Computation does not Help | 2 |
| 18 | 31 | |
| 19 | New Lower Bounds for General Locally Decodable Codes. | 35 |
| 20 | 17 |
About David P. Woodruff
David P. Woodruff is a scholar working on Computational Mathematics, Computational Theory and Mathematics and Artificial Intelligence, having authored 186 papers that have together received 3.1k indexed citations. Recurring topics across this work include Complexity and Algorithms in Graphs (73 papers), Sparse and Compressive Sensing Techniques (69 papers) and Stochastic Gradient Optimization Techniques (64 papers). The work is most often cited by research in Computational Mathematics (263 citations), Computational Theory and Mathematics (1.0k citations) and Artificial Intelligence (1.9k citations). David P. Woodruff has collaborated with scholars based in United States, China and Israel. Frequent co-authors include Kenneth L. Clarkson, Piotr Indyk, Jelani Nelson, Daniel M. Kane, Petros Drineas, Christos Boutsidis, Eric Price, Michael W. Mahoney, Malik Magdon‐Ismail and Morteza Monemizadeh. Their work appears in journals such as Scientific Reports, IEEE Transactions on Information Theory and Journal of the ACM.
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.