Matthew Yu
Impact in
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- Advanced Neural Network Applications
- Advanced Vision and Imaging
- Advanced Image and Video Retrieval Techniques
Papers in
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- Algebraic structures and combinatorial models 6
- Co-authors
- Zijian He (4 shared papers)Péter Vajda (3 shared papers)Peizhao Zhang (3 shared papers)Bichen Wu (2 shared papers)Xiaoliang Dai (2 shared papers)Yuandong Tian (2 shared papers)Joseph E. Gonzalez (2 shared papers)Kan Chen (2 shared papers)
- Journals
- Journal of High Energy Physics (4 papers)Communications in Mathematical Physics (3 papers)Health Equity (1 paper)ACM Transactions on Graphics (1 paper)Frontiers in Immunology (1 paper)
- Partner nations
- United StatesCanadaUnited Kingdom
In The Last Decade
Matthew Yu
17 papers receiving 397 citations
Peers
Comparison fields: 5 of 75
- Computer Vision and Pattern Recognition 207
- Computer Graphics and Computer-Aided Design 26
- Nuclear and High Energy Physics 58
- Artificial Intelligence 140
- Geometry and Topology 37
Countries citing papers authored by Matthew Yu
This map shows the geographic impact of Matthew Yu'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 Matthew Yu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matthew Yu more than expected).
Fields of papers citing papers by Matthew Yu
This network shows the impact of papers produced by Matthew Yu. 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 Matthew Yu. The network helps show where Matthew Yu may publish in the future.
Co-authors
The 25 scholars most cited alongside Matthew Yu, 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 | 2020 | 173 | |
| 2 | 2021 | 55 | |
| 3 | 2020 | 43 | |
| 4 | 2021 | 26 | |
| 5 | 2023 | 26 | |
| 6 | 2020 | 25 | |
| 7 | 2022 | 12 | |
| 8 | 2023 | 11 | |
| 9 | 2023 | 8 | |
| 10 | 2022 | 8 | |
| 11 | 2024 | 7 | |
| 12 | 2023 | 4 | |
| 13 | 2024 | 2 | |
| 14 | 2025 | 2 | |
| 15 | 2025 | 2 | |
| 16 | 2025 | 2 | |
| 17 | 2013 | 1 | |
| 18 | 2025 | 0 |
About Matthew Yu
Matthew Yu is a scholar working on Geometry and Topology, Mathematical Physics, Computer Vision and Pattern Recognition, Atomic and Molecular Physics, and Optics and Nuclear and High Energy Physics, having authored 18 papers that have together received 407 indexed citations. Recurring topics across this work include Algebraic structures and combinatorial models (6 papers), Black Holes and Theoretical Physics (4 papers), Noncommutative and Quantum Gravity Theories (3 papers), Advanced Topics in Algebra (2 papers), Topological Materials and Phenomena (2 papers), T-cell and B-cell Immunology (2 papers), Quantum many-body systems (2 papers) and Image Processing Techniques and Applications (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (207 citations), Computer Graphics and Computer-Aided Design (26 citations), Nuclear and High Energy Physics (58 citations), Artificial Intelligence (140 citations) and Geometry and Topology (37 citations). Matthew Yu has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include Zijian He, Péter Vajda, Peizhao Zhang, Bichen Wu, Xiaoliang Dai, Yuandong Tian, Joseph E. Gonzalez, Kan Chen, Alvin Wan and Tao Xu. Their work appears in journals such as Journal of High Energy Physics, Communications in Mathematical Physics, Health Equity, ACM Transactions on Graphics and Frontiers in Immunology.
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.