Bao Ge

2.4k total citations · 1 hit paper
54 papers, 1.2k citations indexed

About

Bao Ge is a scholar working on Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging and Computer Vision and Pattern Recognition. According to data from OpenAlex, Bao Ge has authored 54 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Cognitive Neuroscience, 23 papers in Radiology, Nuclear Medicine and Imaging and 7 papers in Computer Vision and Pattern Recognition. Recurrent topics in Bao Ge's work include Functional Brain Connectivity Studies (31 papers), Advanced Neuroimaging Techniques and Applications (17 papers) and Neural dynamics and brain function (15 papers). Bao Ge is often cited by papers focused on Functional Brain Connectivity Studies (31 papers), Advanced Neuroimaging Techniques and Applications (17 papers) and Neural dynamics and brain function (15 papers). Bao Ge collaborates with scholars based in China, United States and Singapore. Bao Ge's co-authors include Tianming Liu, Zhengliang Liu, Xiang Li, Zihao Wu, Mengshen He, Sam Fong Yau Li, Dajiang Zhu, Yiheng Liu, Tianle Han and Jiaming Tian and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and NeuroImage.

In The Last Decade

Bao Ge

51 papers receiving 1.2k 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.

Summary of ChatGPT-Related research and perspective towards the future of large language models

2023 408 citations Yiheng Liu, Mengshen He et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Bao Ge China	16	306	262	231	206	201	54	1.2k
Luca Longo Ireland	18	213 0.7×	596 2.3×	80 0.3×	60 0.3×	72 0.4×	84	1.5k
Yixuan Sun China	18	114 0.4×	318 1.2×	100 0.4×	33 0.2×	159 0.8×	69	1.5k
Jiaqi Gong United States	18	40 0.1×	167 0.6×	295 1.3×	72 0.3×	65 0.3×	112	1.2k
Soo Young Lee South Korea	23	159 0.5×	276 1.1×	213 0.9×	50 0.2×	148 0.7×	139	1.6k
Sun‐Hee Kim South Korea	17	124 0.4×	130 0.5×	156 0.7×	27 0.1×	46 0.2×	194	1.2k
Minghui Liu China	16	128 0.4×	74 0.3×	252 1.1×	64 0.3×	121 0.6×	106	1.1k
Md. Amzad Hossain India	16	143 0.5×	90 0.3×	497 2.2×	53 0.3×	97 0.5×	106	1.1k
Zhengliang Liu United States	17	73 0.2×	460 1.8×	36 0.2×	220 1.1×	19 0.1×	51	1.1k
John Liu United States	14	78 0.3×	90 0.3×	479 2.1×	19 0.1×	222 1.1×	43	1.2k
Yanxia Zhao China	9	53 0.2×	94 0.4×	165 0.7×	19 0.1×	106 0.5×	24	672

Countries citing papers authored by Bao Ge

Since Specialization

Citations

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

Fields of papers citing papers by Bao Ge

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Bao Ge

This figure shows the co-authorship network connecting the top 25 collaborators of Bao Ge. A scholar is included among the top collaborators of Bao Ge 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 Bao Ge. Bao Ge 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

Ge, Bao, et al.. (2025). 3D masked autoencoder with spatiotemporal transformer for modeling of 4D fMRI data. Medical Image Analysis. 107(Pt B). 103861–103861.

Liu, Yiheng, Mengshen He, Zhengliang Liu, et al.. (2024). Mapping dynamic spatial patterns of brain function with spatial-wise attention. Journal of Neural Engineering. 21(2). 26005–26005. 2 indexed citations

Wang, Jiaqi, Huawen Hu, Yiheng Liu, et al.. (2024). Large language models for robotics: Opportunities, challenges, and perspectives. 4(1). 52–64. 34 indexed citations

Liu, Yiheng, et al.. (2024). Spatial-temporal convolutional attention for discovering and characterizing functional brain networks in task fMRI. NeuroImage. 287. 120519–120519. 3 indexed citations

He, Mengshen, Shu Zhang, Ning Qiang, et al.. (2023). Accurate corresponding fiber tract segmentation via FiberGeoMap learner with application to autism. Cerebral Cortex. 33(13). 8405–8420. 5 indexed citations

Peng, Yali, et al.. (2023). A two-phase projective dictionary pair learning-based classification scheme for positive and unlabeled learning. Pattern Analysis and Applications. 26(3). 1253–1263. 1 indexed citations

He, Mengshen, et al.. (2023). Multi-head attention-based masked sequence model for mapping functional brain networks. Frontiers in Neuroscience. 17. 1183145–1183145. 12 indexed citations

Qiang, Ning, Qinglin Dong, Jie Gao, et al.. (2022). A Deep Learning Method for Autism Spectrum Disorder Identification Based on Interactions of Hierarchical Brain Networks. SSRN Electronic Journal. 2 indexed citations

Qiang, Ning, Qinglin Dong, Hongtao Liang, et al.. (2021). Modeling and augmenting of fMRI data using deep recurrent variational auto-encoder. Journal of Neural Engineering. 18(4). 0460b6–0460b6. 24 indexed citations

10.

Peng, Yali, et al.. (2021). Dual-Complementary Convolution Network for Remote-Sensing Image Denoising. IEEE Geoscience and Remote Sensing Letters. 19. 1–5. 10 indexed citations

11.

Qiang, Ning, Qinglin Dong, Fangfei Ge, et al.. (2020). Deep Variational Autoencoder for Mapping Functional Brain Networks. IEEE Transactions on Cognitive and Developmental Systems. 13(4). 841–852. 24 indexed citations

12.

Qiang, Ning, Qinglin Dong, Wei Zhang, et al.. (2020). Modeling task-based fMRI data via deep belief network with neural architecture search. Computerized Medical Imaging and Graphics. 83. 101747–101747. 29 indexed citations

13.

Ge, Bao, Xiang Li, Xi Jiang, Yifei Sun, & Tianming Liu. (2018). A Dictionary Learning Approach for Signal Sampling in Task-Based fMRI for Reduction of Big Data. Frontiers in Neuroinformatics. 12. 17–17. 5 indexed citations

14.

Zhao, Yu, Hanbo Chen, Yujie Li, et al.. (2016). Connectome-scale group-wise consistent resting-state network analysis in autism spectrum disorder. NeuroImage Clinical. 12. 23–33. 24 indexed citations

15.

Ge, Bao, Milad Makkie, Shijie Zhao, et al.. (2015). Signal sampling for efficient sparse representation of resting state FMRI data. Brain Imaging and Behavior. 10(4). 1206–1222. 14 indexed citations

16.

Ge, Bao, Yin Tian, Xintao Hu, et al.. (2015). Construction of Multi-Scale Consistent Brain Networks: Methods and Applications. PLoS ONE. 10(4). e0118175–e0118175. 3 indexed citations

17.

Makkie, Milad, Shijie Zhao, Xi Jiang, et al.. (2015). HAFNI-enabled largescale platform for neuroimaging informatics (HELPNI). Brain Informatics. 2(4). 225–238. 10 indexed citations

18.

Ge, Bao, Lei Guo, Tuo Zhang, et al.. (2012). Resting State fMRI-guided Fiber Clustering: Methods and Applications. Neuroinformatics. 11(1). 119–133. 16 indexed citations

19.

Ge, Bao, Lei Guo, Jinglei Lv, et al.. (2011). Resting State fMRI-Guided Fiber Clustering. Lecture notes in computer science. 14(Pt 2). 149–156. 8 indexed citations

20.

Ge, Bao. (1999). AHP Method for High\|Tech Industrialization Risk Assessment. Systems Engineering - Theory & Practice.

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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