David A. Hirshberg
- Computer Vision and Pattern Recognition top 5%
- Computational Mechanics top 5%
- Computer Graphics and Computer-Aided Design top 2%
- Control and Systems Engineering top 10%
- Aerospace Engineering
- Co-authors
- Michael J. BlackAlexander K. H. WeissPeng GuanNeri MerhavRuohan ZhanSusan AtheyEric RachlinMatthew Loper
- Topics
- 3D Shape Modeling and Analysis (4 papers)Computer Graphics and Visualization Techniques (3 papers)Human Motion and Animation (2 papers)
- Cited by
- Computer Graphics and Computer-Aided DesignComputer Vision and Pattern RecognitionComputational Mechanics
- Journals
- IEEE Transactions on Signal ProcessingACM Transactions on GraphicsJournal of Business and Economic Statistics
- Partner nations
- United StatesGermanyIsrael
In The Last Decade
David A. Hirshberg
7 papers receiving 412 citations
Peers
Comparison fields: 5 of 73
- Computer Vision and Pattern Recognition 283
- Computational Mechanics 274
- Computer Graphics and Computer-Aided Design 124
- Control and Systems Engineering 79
- Aerospace Engineering 48
Countries citing papers authored by David A. Hirshberg
This map shows the geographic impact of David A. Hirshberg'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 A. Hirshberg with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David A. Hirshberg more than expected).
Fields of papers citing papers by David A. Hirshberg
This network shows the impact of papers produced by David A. Hirshberg. 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 A. Hirshberg. The network helps show where David A. Hirshberg may publish in the future.
Co-authorship network of co-authors of David A. Hirshberg
This figure shows the co-authorship network connecting the top 25 collaborators of David A. Hirshberg. A scholar is included among the top collaborators of David A. Hirshberg 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 A. Hirshberg. David A. Hirshberg is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 9 | |
| 2 | 1 | |
| 3 | Balancing Out Regression Error: Efficient Treatment Effect Estimation without Smooth Propensities | 0 |
| 4 | 7 | |
| 5 | 183 | |
| 6 | 9 | |
| 7 | 205 | |
| 8 | 12 |
About David A. Hirshberg
David A. Hirshberg is a scholar working on Computer Graphics and Computer-Aided Design, Statistics and Probability and Computational Mechanics, having authored 8 papers that have together received 426 indexed citations. Recurring topics across this work include 3D Shape Modeling and Analysis (4 papers), Computer Graphics and Visualization Techniques (3 papers) and Human Motion and Animation (2 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (124 citations), Computer Vision and Pattern Recognition (283 citations) and Computational Mechanics (274 citations). David A. Hirshberg has collaborated with scholars based in United States, Germany and Israel. Frequent co-authors include Michael J. Black, Alexander K. H. Weiss, Peng Guan, Neri Merhav, Ruohan Zhan, Susan Athey, Eric Rachlin, Matthew Loper, Stefan Wager and Brian D. Corner. Their work appears in journals such as IEEE Transactions on Signal Processing, ACM Transactions on Graphics and Journal of Business and Economic Statistics.
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.