Andy Davis
Impact in
- Hardware and Architecture top 5%
- Parallel Computing and Optimization Techniques
- Embedded Systems Design Techniques
- Computational Mathematics top 10%
Papers in
-
- Stochastic Gradient Optimization Techniques 1
- Domain Adaptation and Few-Shot Learning 1
- Logic, programming, and type systems 1
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- Phosphodiesterase function and regulation 1
- Co-authors
- Jeremy G. Vinter (3 shared papers)Martin Saunders (1 shared paper)Oleksandr Zinenko (1 shared paper)Chris Lattner (1 shared paper)Albert Cohen (1 shared paper)Tatiana Shpeisman (1 shared paper)Jacques A. Pienaar (1 shared paper)Nicolas Vasilache (1 shared paper)
- Journals
- Journal of Computer-Aided Molecular Design (3 papers)Proceedings of the National Academy of Sciences (1 paper)Skin Health and Disease (1 paper)arXiv (Cornell University) (1 paper)
- Partner nations
- United StatesIndiaCanada
In The Last Decade
Andy Davis
8 papers receiving 724 citations
Andy Davis's Hit Papers
Peers
Comparison fields: 5 of 112
- Hardware and Architecture 182
- Computational Mathematics 15
- Software 25
- Artificial Intelligence 206
- Computational Theory and Mathematics 88
Countries citing papers authored by Andy Davis
This map shows the geographic impact of Andy Davis'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 Andy Davis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andy Davis more than expected).
Fields of papers citing papers by Andy Davis
This network shows the impact of papers produced by Andy Davis. 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 Andy Davis. The network helps show where Andy Davis may publish in the future.
Co-authors
The 25 scholars most cited alongside Andy Davis, 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 | 1987 | 284 | |
| 2 | MLIR: Scaling Compiler Infrastructure for Domain Specific Computation Hit paper breakdown → | 2021 | 272 |
| 3 | 2017 | 121 | |
| 4 | 2022 | 31 | |
| 5 | 1987 | 29 | |
| 6 | 2021 | 19 | |
| 7 | 2021 | 2 | |
| 8 | 1988 | 2 |
About Andy Davis
Andy Davis is a scholar working on Artificial Intelligence, Molecular Biology, Computer Vision and Pattern Recognition, Hardware and Architecture and Computational Theory and Mathematics, having authored 8 papers that have together received 760 indexed citations. Recurring topics across this work include Parallel Computing and Optimization Techniques (2 papers), Computational Drug Discovery Methods (2 papers), Advanced Neural Network Applications (2 papers), Stochastic Gradient Optimization Techniques (1 paper), Domain Adaptation and Few-Shot Learning (1 paper), Logic, programming, and type systems (1 paper), Cutaneous Melanoma Detection and Management (1 paper) and Phosphodiesterase function and regulation (1 paper). The work is most often cited by research in Hardware and Architecture (182 citations), Computational Mathematics (15 citations), Software (25 citations), Artificial Intelligence (206 citations) and Computational Theory and Mathematics (88 citations). Andy Davis has collaborated with scholars based in United States, India and Canada. Frequent co-authors include Jeremy G. Vinter, Martin Saunders, Oleksandr Zinenko, Chris Lattner, Albert Cohen, Tatiana Shpeisman, Jacques A. Pienaar, Nicolas Vasilache, Mehdi Amini and Uday Bondhugula. Their work appears in journals such as Journal of Computer-Aided Molecular Design, Proceedings of the National Academy of Sciences, Skin Health and Disease and arXiv (Cornell University).
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.