Deborah Bard
Impact in
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- Scientific Computing and Data Management
- Hardware and Architecture top 10%
- Parallel Computing and Optimization Techniques
Papers in
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- Distributed and Parallel Computing Systems 9
- Advanced Data Storage Technologies 7
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- Scientific Computing and Data Management 8
- Co-authors
- Diana Moise (1 shared paper)Prabhat Prabhat (1 shared paper)Jason Sewall (1 shared paper)Shirley Ho (1 shared paper)Victor C. S. Lee (1 shared paper)Lei Shao (1 shared paper)Siyu He (1 shared paper)Tuomas Kärnä (1 shared paper)
- Journals
- Computer (1 paper)The International Journal of High Performance Computing Applications (1 paper)Astronomy and Computing (1 paper)Concurrency and Computation Practice and Experience (2 papers)Lecture notes in computer science (1 paper)
- Partner nations
- United StatesSpain
In The Last Decade
Deborah Bard
12 papers receiving 147 citations
Peers
Comparison fields: 5 of 37
- Information Systems and Management 43
- Hardware and Architecture 34
- Computer Networks and Communications 57
- Computer Vision and Pattern Recognition 41
- Management Information Systems 9
Countries citing papers authored by Deborah Bard
This map shows the geographic impact of Deborah Bard'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 Deborah Bard with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Deborah Bard more than expected).
Fields of papers citing papers by Deborah Bard
This network shows the impact of papers produced by Deborah Bard. 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 Deborah Bard. The network helps show where Deborah Bard may publish in the future.
Co-authors
The 25 scholars most cited alongside Deborah Bard, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 76 | |
| 2 | 2021 | 14 | |
| 3 | 2020 | 11 | |
| 4 | 2024 | 11 | |
| 5 | 2012 | 11 | |
| 6 | 2021 | 8 | |
| 7 | 2019 | 5 | |
| 8 | 2022 | 5 | |
| 9 | 2024 | 3 | |
| 10 | 2021 | 3 | |
| 11 | 2020 | 1 | |
| 12 | 2017 | 1 | |
| 13 | 2023 | 0 |
About Deborah Bard
Deborah Bard is a scholar working on Computer Networks and Communications, Information Systems and Management, Artificial Intelligence, Hardware and Architecture and Nuclear and High Energy Physics, having authored 13 papers that have together received 149 indexed citations. Recurring topics across this work include Distributed and Parallel Computing Systems (9 papers), Scientific Computing and Data Management (8 papers), Advanced Data Storage Technologies (7 papers), Particle physics theoretical and experimental studies (2 papers), Computational Physics and Python Applications (2 papers), Parallel Computing and Optimization Techniques (2 papers), Cloud Computing and Resource Management (1 paper) and Enzyme Structure and Function (1 paper). The work is most often cited by research in Information Systems and Management (43 citations), Hardware and Architecture (34 citations), Computer Networks and Communications (57 citations), Computer Vision and Pattern Recognition (41 citations) and Management Information Systems (9 citations). Deborah Bard has collaborated with scholars based in United States and Spain. Frequent co-authors include Diana Moise, Prabhat Prabhat, Jason Sewall, Shirley Ho, Victor C. S. Lee, Lei Shao, Siyu He, Tuomas Kärnä, S. J. Pennycook and Johannes Blaschke. Their work appears in journals such as Computer, The International Journal of High Performance Computing Applications, Astronomy and Computing, Concurrency and Computation Practice and Experience and Lecture notes in computer science.
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.