Bowen Liu

2.8k total citations · 1 hit paper
132 papers, 1.1k citations indexed

About

Bowen Liu is a scholar working on Electrical and Electronic Engineering, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Bowen Liu has authored 132 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 41 papers in Electrical and Electronic Engineering, 34 papers in Artificial Intelligence and 24 papers in Computer Vision and Pattern Recognition. Recurrent topics in Bowen Liu's work include Blockchain Technology Applications and Security (11 papers), IoT and Edge/Fog Computing (8 papers) and Caching and Content Delivery (7 papers). Bowen Liu is often cited by papers focused on Blockchain Technology Applications and Security (11 papers), IoT and Edge/Fog Computing (8 papers) and Caching and Content Delivery (7 papers). Bowen Liu collaborates with scholars based in China, United States and Singapore. Bowen Liu's co-authors include Aixuan Li, Jing Zhang, Yuchao Dai, Deng-Ping Fan, Yunqiu Lv, Nick Barnes, Hun-Seok Kim, Paweł Szałachowski, Andrew C. Scheiner and Henry F. Schaefer and has published in prestigious journals such as Journal of the American Chemical Society, Advanced Materials and SHILAP Revista de lepidopterología.

In The Last Decade

Bowen Liu

108 papers receiving 1.0k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Simultaneously Localize, Segment and Rank the Camouflaged Objects

2021 270 citations Bowen Liu et al. profile →

Peers

Bowen Liu

CVPR

EEE

AI

IS

CNC

Bartolomeo Montrucchio Italy

Xian Du United States

Jianliang Gao China

Yixiang Chen China

Xin Liu China

Xiang Fei China

Hyun Kim South Korea

Xiaojun Ye China

Wei Niu United States

Bartolomeo Montrucchio Italy

Bowen Liu

269 ×0.7

CVPR

445 ×1.9

EEE

112 ×0.6

AI

131 ×1.2

IS

412 ×4.5

CNC

Citations per year, relative to Bowen Liu Bowen Liu (= 1×) peers Bartolomeo Montrucchio

Countries citing papers authored by Bowen Liu

Since Specialization

Citations

This map shows the geographic impact of Bowen 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 Bowen Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bowen Liu more than expected).

Fields of papers citing papers by Bowen Liu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Bowen 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 Bowen Liu. The network helps show where Bowen Liu may publish in the future.

Co-authorship network of co-authors of Bowen Liu

This figure shows the co-authorship network connecting the top 25 collaborators of Bowen Liu. A scholar is included among the top collaborators of Bowen Liu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Bowen Liu. Bowen Liu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Yang, Mingyu, et al.. (2025). Diffusion-Aided Joint Source Channel Coding for High Realism Wireless Image Transmission. SHILAP Revista de lepidopterología. 3. 1227–1243. 2 indexed citations

2.

Liu, Bowen, et al.. (2025). ViG3D-UNet: Volumetric Vascular Connectivity-Aware Segmentation via 3D Vision Graph Representation. IEEE Journal of Biomedical and Health Informatics. 30(3). 2537–2549.

3.

Lin, Wei, et al.. (2025). RTS-ViT: Real-Time Share Vision Transformer for Image Classification. IEEE Journal of Biomedical and Health Informatics. 29(5). 3576–3586. 2 indexed citations

4.

Zhang, Zhiqian, et al.. (2025). Fracture loads of ISRM-suggested notched semi-circular bend rock specimens using finite fracture mechanics. Theoretical and Applied Fracture Mechanics. 139. 104997–104997.

5.

Liu, Bowen, et al.. (2024). Experimental study on the flow electrification of liquid nitrogen in turbulent flow. Cryogenics. 140. 103853–103853. 1 indexed citations

6.

Song, Hong, et al.. (2024). MSLR: A Self-supervised Representation Learning Method for Tabular Data Based on Multi-scale Ladder Reconstruction. Information Sciences. 660. 120108–120108. 1 indexed citations

7.

Xu, Xiaoyu, Yang Gao, Yucheng Zhu, et al.. (2024). Predictive and Prognostic Potentials of Lymphocyte-C-Reactive Protein Ratio Upon Hospitalization in Adult Patients with Acute Pancreatitis. Journal of Inflammation Research. Volume 17. 1659–1669. 2 indexed citations

8.

Liu, Genggeng, Zhengyang Chen, Zhisheng Chen, et al.. (2024). Physical design for microfluidic biochips considering actual volume management and channel storage. Integration. 98. 102228–102228.

9.

Liu, Bowen, et al.. (2024). Research on the Price Prediction Model of the Used New Energy Vehicles Based on PCA-PSO-BP Neural Network. 1745–1748.

10.

Wang, Xuesong, C. L. Philip Chen, Long Chen, et al.. (2024). Cross-View Representation Learning-Based Deep Multiview Clustering With Adaptive Graph Constraint. IEEE Transactions on Neural Networks and Learning Systems. 36(7). 12895–12909. 1 indexed citations

11.

Zhang, Qirui, Li Xu, Ang Cao, et al.. (2024). AIMMI: Audio and Image Multi-Modal Intelligence via a Low-Power SoC With 2-MByte On-Chip MRAM for IoT Devices. IEEE Journal of Solid-State Circuits. 59(10). 3488–3501.

12.

Song, Hong, et al.. (2023). A joint learning method for incomplete and imbalanced data in electronic health record based on generative adversarial networks. Computers in Biology and Medicine. 168. 107687–107687. 7 indexed citations

13.

Wang, Chunzhi, Lu Wang, Siwei Wei, et al.. (2023). STN-GCN: Spatial and Temporal Normalization Graph Convolutional Neural Networks for Traffic Flow Forecasting. Electronics. 12(14). 3158–3158. 13 indexed citations

14.

Liu, Bowen, et al.. (2023). Flow electrification characteristics of liquid hydrogen in pipe flow. International Journal of Hydrogen Energy. 48(48). 18526–18539. 5 indexed citations

15.

Liu, Bowen, et al.. (2023). Solder Selection Simulation Of IGBT Module Based On Thermal - Mechanical Coupling Field. 1–5. 1 indexed citations

16.

Liu, Bowen, et al.. (2023). An effective data placement strategy for IIoT applications. Concurrency and Computation Practice and Experience. 36(10).

17.

Wang, Z., et al.. (2022). Power System Fault Diagnosis Method Based on Deep Reinforcement Learning. Energies. 15(20). 7639–7639. 8 indexed citations

18.

Bowen, Judy, Benjamin Weyers, & Bowen Liu. (2022). Creating Formal Models from Informal Design Artefacts. International Journal of Human-Computer Interaction. 39(15). 3141–3158. 4 indexed citations

19.

Li, Ziyun, Zhehong Wang, Li Xu, et al.. (2020). RRAM-DNN: An RRAM and Model-Compression Empowered All-Weights-On-Chip DNN Accelerator. IEEE Journal of Solid-State Circuits. 56(4). 1105–1115. 23 indexed citations

20.

Dai, Yongshou, Bowen Liu, Ligang Li, et al.. (2018). Sea-sky-line detection based on local Otsu segmentation and Hough transform. Guangdian gongcheng. 45(7). 180039. 13 indexed citations

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.

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