Shaoli Liu
Impact in
- Computational Mathematics top 2%
- Hardware and Architecture top 1%
- Parallel Computing and Optimization Techniques
Papers in
-
- Advanced Neural Network Applications 22
- Optical measurement and interference techniques 14
- Image and Object Detection Techniques 7
- Advanced Vision and Imaging 7
- Catalysis 10
- Co-authors
- Baoquan DingYunji ChenTianshi ChenQiao JiangJianbing LiuShijin ZhangGuangjun NieYinlong Zhang
- Journals
- Measurement (5 papers)The Journal of Physical Chemistry C (4 papers)Fish & Shellfish Immunology (4 papers)Journal of Molecular Modeling (4 papers)ACS Applied Materials & Interfaces (4 papers)
- Partner nations
- ChinaUnited StatesGermany
In The Last Decade
Shaoli Liu
131 papers receiving 7.8k citations
Hit Papers
Peers
Comparison fields: 5 of 176
- Computational Mathematics 73
- Hardware and Architecture 618
- Computer Vision and Pattern Recognition 1.8k
- Biomaterials 591
- Molecular Biology 3.1k
Countries citing papers authored by Shaoli Liu
This map shows the geographic impact of Shaoli Liu'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 Shaoli Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shaoli Liu more than expected).
Fields of papers citing papers by Shaoli Liu
This network shows the impact of papers produced by Shaoli Liu. 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 Shaoli Liu. The network helps show where Shaoli Liu may publish in the future.
Co-authors
The 25 scholars most cited alongside Shaoli Liu, 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 | 2024 | 3 | |
| 2 | 2024 | 1 | |
| 3 | 2024 | 3 | |
| 4 | 2023 | 0 | |
| 5 | 2023 | 1 | |
| 6 | 2023 | 5 | |
| 7 | 2023 | 11 | |
| 8 | 2023 | 1 | |
| 9 | 2023 | 6 | |
| 10 | 2023 | 2 | |
| 11 | 2022 | 9 | |
| 12 | 2021 | 12 | |
| 13 | Bacterial cytoplasmic membranes synergistically enhance the antitumor activity of autologous cancer vaccines Hit paper breakdown → | 2021 | 186 |
| 14 | 2020 | 35 | |
| 15 | 2019 | 17 | |
| 16 | 2018 | 11 | |
| 17 | 2017 | 8 | |
| 18 | 2016 | 9 | |
| 19 | 2016 | 76 | |
| 20 | 2016 | 11 |
About Shaoli Liu
Shaoli Liu is a scholar working on Computer Vision and Pattern Recognition, Catalysis, Process Chemistry and Technology, Hardware and Architecture and Geology, having authored 135 papers that have together received 8.0k indexed citations. Recurring topics across this work include Advanced Neural Network Applications (22 papers), Advanced biosensing and bioanalysis techniques (19 papers), RNA Interference and Gene Delivery (18 papers), Advanced Memory and Neural Computing (14 papers), Optical measurement and interference techniques (14 papers), Catalytic Processes in Materials Science (11 papers), Image and Object Detection Techniques (7 papers) and Advanced Vision and Imaging (7 papers). The work is most often cited by research in Computational Mathematics (73 citations), Hardware and Architecture (618 citations), Computer Vision and Pattern Recognition (1.8k citations), Biomaterials (591 citations) and Molecular Biology (3.1k citations). Shaoli Liu has collaborated with scholars based in China, United States and Germany. Frequent co-authors include Baoquan Ding, Yunji Chen, Tianshi Chen, Qiao Jiang, Jianbing Liu, Shijin Zhang, Guangjun Nie, Yinlong Zhang, Tao Luo and Shuai Zhao. Their work appears in journals such as Measurement, The Journal of Physical Chemistry C, Fish & Shellfish Immunology, Journal of Molecular Modeling and ACS Applied Materials & Interfaces.
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.