Shuyang Dai
- Materials Chemistry top 10%
- Microstructure and mechanical properties 7
- Graphene research and applications 4
- Cancer Research top 10%
- Hepatology top 10%
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- Pediatric Hepatobiliary Diseases and Treatments 5
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- Generative Adversarial Networks and Image Synthesis 5
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- Radiation Therapy and Dosimetry 5
- Gallbladder and Bile Duct Disorders 4
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- Genetic Associations and Epidemiology 4
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- Liver Disease Diagnosis and Treatment 4
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Shuyang Dai
61 papers receiving 1.4k citations
Peers
Comparison fields: 5 of 137
- Materials Chemistry 704
- Cancer Research 174
- Hepatology 74
- Atomic and Molecular Physics, and Optics 237
- Polymers and Plastics 76
Countries citing papers authored by Shuyang Dai
This map shows the geographic impact of Shuyang Dai'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 Shuyang Dai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shuyang Dai more than expected).
Fields of papers citing papers by Shuyang Dai
This network shows the impact of papers produced by Shuyang Dai. 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 Shuyang Dai. The network helps show where Shuyang Dai may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Shuyang Dai, 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 | 2025 | 0 | |
| 2 | 2024 | 7 | |
| 3 | 2024 | 0 | |
| 4 | 2024 | 2 | |
| 5 | 2024 | 1 | |
| 6 | 2024 | 1 | |
| 7 | 2024 | 1 | |
| 8 | 2023 | 36 | |
| 9 | 2023 | 2 | |
| 10 | 2022 | 7 | |
| 11 | 2022 | 6 | |
| 12 | 2021 | 1 | |
| 13 | 2020 | 94 | |
| 14 | Variational annealing of GANs: A Langevin perspective | 2019 | 1 |
| 15 | On Fenchel Mini-Max Learning | 2019 | 1 |
| 16 | Symmetric Variational Autoencoder and Connections to Adversarial Learning | 2018 | 12 |
| 17 | JointGAN: Multi-Domain Joint Distribution Learning with Generative Adversarial Nets | 2018 | 3 |
| 18 | 2018 | 4 | |
| 19 | 2017 | 18 | |
| 20 | 2015 | 288 |
About Shuyang Dai
Shuyang Dai is a scholar working on Radiation, Statistics, Probability and Uncertainty and Pulmonary and Respiratory Medicine, having authored 66 papers that have together received 1.4k indexed citations. Recurring topics across this work include Microstructure and mechanical properties (7 papers), Pediatric Hepatobiliary Diseases and Treatments (5 papers), Generative Adversarial Networks and Image Synthesis (5 papers), Radiation Therapy and Dosimetry (5 papers), Graphene research and applications (4 papers), Genetic Associations and Epidemiology (4 papers), Liver Disease Diagnosis and Treatment (4 papers) and Gallbladder and Bile Duct Disorders (4 papers). The work is most often cited by research in Materials Chemistry (704 citations), Cancer Research (174 citations) and Hepatology (74 citations). Shuyang Dai has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include David J. Srolovitz, Yang Xiang, Jiarui Yang, Xide Li, Wen Wang, Quanshui Zheng, Yijie Xia, Jian Han, Songsong Zhou and Jianwei Sun. Their work appears in journals such as Nature Communications, Nano Letters and Bioinformatics.
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.