Eddie Yan
Impact in
- Computational Mathematics top 5%
- Hardware and Architecture top 5%
- Parallel Computing and Optimization Techniques
Papers in
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- Advanced Neural Network Applications 3
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- Parallel Computing and Optimization Techniques 4
- Co-authors
- Qingshan Wei (2 shared papers)Aydogan Özcan (2 shared papers)Derek Tseng (2 shared papers)Luís Ceze (3 shared papers)Steve Feng (2 shared papers)Arvind Krishnamurthy (2 shared papers)Carlos Guestrin (2 shared papers)Thierry Moreau (2 shared papers)
- Journals
- ACS Nano (2 papers)Pharmaceuticals (1 paper)Topics in Cognitive Science (1 paper)arXiv (Cornell University) (1 paper)Operating Systems Design and Implementation (1 paper)
- Partner nations
- United StatesUnited KingdomChina
In The Last Decade
Eddie Yan
10 papers receiving 1.1k citations
Eddie Yan's Hit Papers
Peers
Comparison fields: 5 of 134
- Computational Mathematics 40
- Hardware and Architecture 225
- Computer Vision and Pattern Recognition 327
- Artificial Intelligence 266
- Biomedical Engineering 326
Countries citing papers authored by Eddie Yan
This map shows the geographic impact of Eddie Yan'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 Eddie Yan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eddie Yan more than expected).
Fields of papers citing papers by Eddie Yan
This network shows the impact of papers produced by Eddie Yan. 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 Eddie Yan. The network helps show where Eddie Yan may publish in the future.
Co-authors
The 25 scholars most cited alongside Eddie Yan, 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 | TVM: an automated end-to-end optimizing compiler for deep learning Hit paper breakdown → | 2018 | 522 |
| 2 | 2014 | 332 | |
| 3 | 2014 | 144 | |
| 4 | 2017 | 38 | |
| 5 | Learning to Optimize Tensor Programs | 2018 | 29 |
| 6 | 2022 | 16 | |
| 7 | 2015 | 12 | |
| 8 | Customizing Progressive JPEG for Efficient Image Storage. | 2017 | 6 |
| 9 | 2020 | 3 | |
| 10 | 2021 | 2 |
About Eddie Yan
Eddie Yan is a scholar working on Computer Vision and Pattern Recognition, Hardware and Architecture, Molecular Biology, Artificial Intelligence and Computer Networks and Communications, having authored 10 papers that have together received 1.1k indexed citations. Recurring topics across this work include Parallel Computing and Optimization Techniques (4 papers), Advanced Neural Network Applications (3 papers), Advanced biosensing and bioanalysis techniques (2 papers), Digital Games and Media (2 papers), Advanced Data Storage Technologies (2 papers), Biosensors and Analytical Detection (2 papers), Gambling Behavior and Treatments (2 papers) and Artificial Intelligence in Games (1 paper). The work is most often cited by research in Computational Mathematics (40 citations), Hardware and Architecture (225 citations), Computer Vision and Pattern Recognition (327 citations), Artificial Intelligence (266 citations) and Biomedical Engineering (326 citations). Eddie Yan has collaborated with scholars based in United States, United Kingdom and China. Frequent co-authors include Qingshan Wei, Aydogan Özcan, Derek Tseng, Luís Ceze, Steve Feng, Arvind Krishnamurthy, Carlos Guestrin, Thierry Moreau, Tianqi Chen and Ziheng Jiang. Their work appears in journals such as ACS Nano, Pharmaceuticals, Topics in Cognitive Science, arXiv (Cornell University) and Operating Systems Design and Implementation.
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.