Bin Bi
Impact in
- Pollution top 2%
- Pharmaceutical and Antibiotic Environmental Impacts
-
- Constructed Wetlands for Wastewater Treatment
Papers in ⓘ
-
- Multimodal Machine Learning Applications 9
- Co-authors
- Shaoyong Lu (7 shared papers)Xiaohui Liu (5 shared papers)Xiaochun Guo (5 shared papers)Ying Liu (3 shared papers)Beidou Xi (2 shared papers)Zhi Wang (1 shared paper)Jian Zhang (1 shared paper)Songfang Huang (8 shared papers)
- Journals
- Environmental Pollution (2 papers)Chemosphere (1 paper)RSC Advances (1 paper)Environmental Science and Pollution Research (1 paper)Frontiers in Environmental Science (1 paper)
- Partner nations
- United StatesChinaHong Kong
In The Last Decade
Bin Bi
30 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 119
- Pollution 410
- Industrial and Manufacturing Engineering 148
- Molecular Medicine 76
- Applied Microbiology and Biotechnology 23
- Computer Vision and Pattern Recognition 221
Countries citing papers authored by Bin Bi
This map shows the geographic impact of Bin Bi'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 Bin Bi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bin Bi more than expected).
Fields of papers citing papers by Bin Bi
This network shows the impact of papers produced by Bin Bi. 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 Bin Bi. The network helps show where Bin Bi may publish in the future.
Co-authors
The 25 scholars most cited alongside Bin Bi, 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 31 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 268 | |
| 2 | 2018 | 241 | |
| 3 | 2022 | 90 | |
| 4 | 2013 | 79 | |
| 5 | 2021 | 56 | |
| 6 | 2021 | 52 | |
| 7 | 2014 | 51 | |
| 8 | 2019 | 30 | |
| 9 | 2018 | 26 | |
| 10 | 2015 | 22 | |
| 11 | 2021 | 20 | |
| 12 | 2019 | 20 | |
| 13 | 2022 | 19 | |
| 14 | 2016 | 18 | |
| 15 | 2012 | 15 | |
| 16 | IDST at TREC 2019 Deep Learning Track: Deep Cascade Ranking with Generation-based Document Expansion and Pre-trained Language Modeling. | 2019 | 14 |
| 17 | 2021 | 10 | |
| 18 | 2011 | 10 | |
| 19 | 2021 | 9 | |
| 20 | 2023 | 7 |
About Bin Bi
Bin Bi is a scholar working on Health Informatics, Computer Vision and Pattern Recognition, Artificial Intelligence, Applied Microbiology and Biotechnology and Biological Psychiatry, having authored 31 papers that have together received 1.1k indexed citations. Recurring topics across this work include Topic Modeling (10 papers), Natural Language Processing Techniques (9 papers), Multimodal Machine Learning Applications (9 papers), Recommender Systems and Techniques (6 papers), Text and Document Classification Technologies (3 papers), Pharmaceutical and Antibiotic Environmental Impacts (3 papers), Domain Adaptation and Few-Shot Learning (3 papers) and Advanced Text Analysis Techniques (3 papers). The work is most often cited by research in Pollution (410 citations), Industrial and Manufacturing Engineering (148 citations), Molecular Medicine (76 citations), Applied Microbiology and Biotechnology (23 citations) and Computer Vision and Pattern Recognition (221 citations). Bin Bi has collaborated with scholars based in United States, China and Hong Kong. Frequent co-authors include Shaoyong Lu, Xiaohui Liu, Xiaochun Guo, Ying Liu, Beidou Xi, Zhi Wang, Jian Zhang, Songfang Huang, Junghoo Cho and Pan Qin. Their work appears in journals such as Environmental Pollution, Chemosphere, RSC Advances, Environmental Science and Pollution Research and Frontiers in Environmental Science.
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.