Lisha Chen
Impact in
- Pollution top 5%
- Microbial bioremediation and biosurfactants
- Statistics and Probability top 2%
- Statistical Methods and Inference
Papers in
-
- Microbial bioremediation and biosurfactants 6
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- Robotic Mechanisms and Dynamics 5
- Co-authors
- Andreas Buja (4 shared papers)Jianhua Z. Huang (2 shared papers)Rongjie Kang (12 shared papers)Jian S. Dai (6 shared papers)Hongbing Yao (3 shared papers)David T. Branson (4 shared papers)Heike Hofmann (1 shared paper)Deborah F. Swayne (1 shared paper)
- Journals
- Journal of the American Statistical Association (4 papers)Medicine (3 papers)Scientific Reports (2 papers)Environmental Science and Pollution Research (2 papers)Cancer Letters (2 papers)
- Partner nations
- ChinaUnited StatesItaly
In The Last Decade
Lisha Chen
136 papers receiving 3k citations
Peers
Comparison fields: 5 of 179
- Pollution 189
- Statistics and Probability 186
- Computational Mathematics 9
- Computer Vision and Pattern Recognition 288
- Cancer Research 133
Countries citing papers authored by Lisha Chen
This map shows the geographic impact of Lisha Chen'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 Lisha Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lisha Chen more than expected).
Fields of papers citing papers by Lisha Chen
This network shows the impact of papers produced by Lisha Chen. 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 Lisha Chen. The network helps show where Lisha Chen may publish in the future.
Co-authors
The 25 scholars most cited alongside Lisha Chen, 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 144 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2008 | 221 | |
| 2 | 2003 | 180 | |
| 3 | 2012 | 165 | |
| 4 | 1999 | 160 | |
| 5 | 2009 | 140 | |
| 6 | 2017 | 112 | |
| 7 | 2020 | 100 | |
| 8 | 2016 | 93 | |
| 9 | 2024 | 83 | |
| 10 | 2009 | 68 | |
| 11 | 2011 | 63 | |
| 12 | 2014 | 61 | |
| 13 | 2021 | 60 | |
| 14 | 2018 | 54 | |
| 15 | 2015 | 51 | |
| 16 | 2016 | 50 | |
| 17 | 2019 | 49 | |
| 18 | 2012 | 46 | |
| 19 | 2014 | 43 | |
| 20 | 2023 | 42 |
About Lisha Chen
Lisha Chen is a scholar working on Pollution, Control and Systems Engineering, Biomedical Engineering, Artificial Intelligence and Pharmacology, having authored 144 papers that have together received 3.1k indexed citations. Recurring topics across this work include Soft Robotics and Applications (13 papers), Control Systems in Engineering (7 papers), Microbial bioremediation and biosurfactants (6 papers), Multilevel Inverters and Converters (5 papers), Robotic Mechanisms and Dynamics (5 papers), S100 Proteins and Annexins (5 papers), Advanced Photocatalysis Techniques (4 papers) and Statistical Methods and Inference (4 papers). The work is most often cited by research in Pollution (189 citations), Statistics and Probability (186 citations), Computational Mathematics (9 citations), Computer Vision and Pattern Recognition (288 citations) and Cancer Research (133 citations). Lisha Chen has collaborated with scholars based in China, United States and Italy. Frequent co-authors include Andreas Buja, Jianhua Z. Huang, Rongjie Kang, Jian S. Dai, Hongbing Yao, David T. Branson, Heike Hofmann, Deborah F. Swayne, Michael L. Littman and Nathaniel Dean. Their work appears in journals such as Journal of the American Statistical Association, Medicine, Scientific Reports, Environmental Science and Pollution Research and Cancer Letters.
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.