Bai Wang
Impact in
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- Complex Network Analysis Techniques
- Opinion Dynamics and Social Influence
- Artificial Intelligence top 2%
- Advanced Graph Neural Networks
- Topic Modeling
Papers in
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- Advanced Graph Neural Networks 18
- Topic Modeling 6
-
- Complex Network Analysis Techniques 34
- Opinion Dynamics and Social Influence 11
- Co-authors
- Bin Wu (29 shared papers)Chuan Shi (14 shared papers)Nan Du (6 shared papers)Shaohua Fan (4 shared papers)Liutong Xu (8 shared papers)Xiao Wang (6 shared papers)Xin Pei (2 shared papers)Xiao Wang (1 shared paper)
- Journals
- Fish & Shellfish Immunology (5 papers)Aquaculture (3 papers)Computer Aided Surgery (2 papers)IEEE Access (2 papers)Agronomy (2 papers)
- Partner nations
- ChinaUnited StatesAustria
In The Last Decade
Bai Wang
100 papers receiving 1.5k citations
Peers
Comparison fields: 5 of 140
- Statistical and Nonlinear Physics 391
- Artificial Intelligence 605
- Information Systems 295
- Computer Vision and Pattern Recognition 265
- Aquatic Science 93
Countries citing papers authored by Bai Wang
This map shows the geographic impact of Bai Wang'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 Bai Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bai Wang more than expected).
Fields of papers citing papers by Bai Wang
This network shows the impact of papers produced by Bai Wang. 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 Bai Wang. The network helps show where Bai Wang may publish in the future.
Co-authors
The 25 scholars most cited alongside Bai Wang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 110 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 141 | |
| 2 | 2007 | 126 | |
| 3 | 2002 | 123 | |
| 4 | 2021 | 72 | |
| 5 | 2015 | 58 | |
| 6 | 2023 | 55 | |
| 7 | 2020 | 48 | |
| 8 | 2006 | 47 | |
| 9 | 2009 | 35 | |
| 10 | 2019 | 28 | |
| 11 | 2022 | 28 | |
| 12 | 2021 | 26 | |
| 13 | 2023 | 26 | |
| 14 | 2020 | 25 | |
| 15 | 2023 | 24 | |
| 16 | 2022 | 24 | |
| 17 | 2018 | 24 | |
| 18 | 2006 | 24 | |
| 19 | 2019 | 23 | |
| 20 | 2012 | 20 |
About Bai Wang
Bai Wang is a scholar working on Artificial Intelligence, Statistical and Nonlinear Physics, Information Systems, Computer Networks and Communications and Aquatic Science, having authored 110 papers that have together received 1.5k indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (34 papers), Advanced Graph Neural Networks (18 papers), Echinoderm biology and ecology (13 papers), Opinion Dynamics and Social Influence (11 papers), Recommender Systems and Techniques (8 papers), Invertebrate Immune Response Mechanisms (7 papers), Distributed and Parallel Computing Systems (7 papers) and Topic Modeling (6 papers). The work is most often cited by research in Statistical and Nonlinear Physics (391 citations), Artificial Intelligence (605 citations), Information Systems (295 citations), Computer Vision and Pattern Recognition (265 citations) and Aquatic Science (93 citations). Bai Wang has collaborated with scholars based in China, United States and Austria. Frequent co-authors include Bin Wu, Chuan Shi, Nan Du, Shaohua Fan, Liutong Xu, Xiao Wang, Xin Pei, Xiao Wang, Ken Lin and Philip S. Yu. Their work appears in journals such as Fish & Shellfish Immunology, Aquaculture, Computer Aided Surgery, IEEE Access and Agronomy.
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.