Bowen Tan
- Artificial Intelligence top 5%
- Topic Modeling 12
- Natural Language Processing Techniques 9
- Speech and dialogue systems 6
- Advanced Text Analysis Techniques 3
- Endocrine and Autonomic Systems top 10%
- Regulation of Appetite and Obesity 3
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- Neurotransmitter Receptor Influence on Behavior 2
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- Eicosanoids and Hypertension Pharmacology 2
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- Computational Drug Discovery Methods 2
- Journals
- Cell Metabolism (1 paper)Scientific Reports (1 paper)Journal of Computing and Information Science in Engineering (1 paper)
- Partner nations
- ChinaUnited StatesUnited Arab Emirates
In The Last Decade
Bowen Tan
35 papers receiving 543 citations
Peers
Comparison fields: 5 of 110
- Artificial Intelligence 306
- Endocrine and Autonomic Systems 58
- Behavioral Neuroscience 19
- Computer Vision and Pattern Recognition 73
- Cellular and Molecular Neuroscience 64
Countries citing papers authored by Bowen Tan
This map shows the geographic impact of Bowen Tan'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 Bowen Tan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bowen Tan more than expected).
Fields of papers citing papers by Bowen Tan
This network shows the impact of papers produced by Bowen Tan. 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 Bowen Tan. The network helps show where Bowen Tan may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Bowen Tan, 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 | 2 | |
| 2 | 2025 | 6 | |
| 3 | 2025 | 0 | |
| 4 | 2024 | 26 | |
| 5 | 2024 | 1 | |
| 6 | 2024 | 2 | |
| 7 | 2023 | 10 | |
| 8 | 2023 | 0 | |
| 9 | 2023 | 13 | |
| 10 | 2023 | 0 | |
| 11 | 2022 | 7 | |
| 12 | 2021 | 40 | |
| 13 | 2021 | 39 | |
| 14 | 2021 | 1 | |
| 15 | 2020 | 54 | |
| 16 | 2020 | 24 | |
| 17 | Connecting the Dots Between MLE and RL for Sequence Generation | 2019 | 5 |
| 18 | 2019 | 55 | |
| 19 | Structured Dialogue Policy with Graph Neural Networks | 2018 | 14 |
| 20 | 2017 | 1 |
About Bowen Tan
Bowen Tan is a scholar working on Endocrine and Autonomic Systems, Artificial Intelligence, Process Chemistry and Technology, Computer Graphics and Computer-Aided Design and Biochemistry, having authored 39 papers that have together received 561 indexed citations. Recurring topics across this work include Topic Modeling (12 papers), Natural Language Processing Techniques (9 papers), Speech and dialogue systems (6 papers), Advanced Text Analysis Techniques (3 papers), Regulation of Appetite and Obesity (3 papers), Eicosanoids and Hypertension Pharmacology (2 papers), Neurotransmitter Receptor Influence on Behavior (2 papers) and Computational Drug Discovery Methods (2 papers). The work is most often cited by research in Artificial Intelligence (306 citations), Endocrine and Autonomic Systems (58 citations), Behavioral Neuroscience (19 citations), Computer Vision and Pattern Recognition (73 citations) and Cellular and Molecular Neuroscience (64 citations). Bowen Tan has collaborated with scholars based in China, United States and United Arab Emirates. Frequent co-authors include Eric P. Xing, Zhiting Hu, Kai Yu, Jeffrey M. Friedman, Lu Chen, Chi Wang, Su Zhu, Lisa E. Pomeranz, Estefania P. Azevedo and Marc Schneeberger. Their work appears in journals such as Cell Metabolism, Scientific Reports, Journal of Computing and Information Science in Engineering, Research and IEEE/ACM Transactions on Audio Speech and Language Processing.
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.