Hongbo Jia

4.8k total citations · 1 hit paper
82 papers, 2.6k citations indexed

About

Hongbo Jia is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Biophysics. According to data from OpenAlex, Hongbo Jia has authored 82 papers receiving a total of 2.6k indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Cognitive Neuroscience, 22 papers in Cellular and Molecular Neuroscience and 14 papers in Biophysics. Recurrent topics in Hongbo Jia's work include Neural dynamics and brain function (21 papers), Neuroscience and Neuropharmacology Research (18 papers) and Advanced Fluorescence Microscopy Techniques (13 papers). Hongbo Jia is often cited by papers focused on Neural dynamics and brain function (21 papers), Neuroscience and Neuropharmacology Research (18 papers) and Advanced Fluorescence Microscopy Techniques (13 papers). Hongbo Jia collaborates with scholars based in China, Germany and United States. Hongbo Jia's co-authors include Arthur Konnerth, Xiaowei Chen, Nathalie L. Rochefort, Xuhui Luo, Bert Sakmann, Dapeng Yu, Zsuzsanna Varga, Rongming Wang, Dapeng Yu and Xihong Chen and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Nature Communications.

In The Last Decade

Hongbo Jia

78 papers receiving 2.5k citations

Hit Papers

Fast high-resolution miniature two-photon microscopy for ... 2017 2026 2020 2023 2017 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Hongbo Jia China 25 977 785 596 574 420 82 2.6k
Hideki Tamura Japan 33 740 0.8× 286 0.4× 560 0.9× 772 1.3× 667 1.6× 210 4.5k
Yael Hanein Israel 34 1.5k 1.5× 567 0.7× 1.1k 1.8× 603 1.1× 1.3k 3.2× 123 3.5k
Shy Shoham Israel 36 1.6k 1.6× 1.4k 1.7× 286 0.5× 321 0.6× 2.2k 5.1× 100 4.5k
Timothy J. Gardner United States 28 646 0.7× 566 0.7× 541 0.9× 357 0.6× 340 0.8× 71 2.4k
Lun‐De Liao Taiwan 32 825 0.8× 1.2k 1.5× 495 0.8× 619 1.1× 1.9k 4.6× 141 3.9k
Jing Yuan China 29 565 0.6× 453 0.6× 157 0.3× 323 0.6× 458 1.1× 177 3.0k
Hirokazu Takahashi Japan 24 697 0.7× 1.1k 1.4× 488 0.8× 376 0.7× 395 0.9× 175 2.5k
Shoogo Ueno Japan 32 627 0.6× 1.6k 2.0× 297 0.5× 115 0.2× 918 2.2× 273 4.5k
Corrado Calı Italy 23 573 0.6× 199 0.3× 294 0.5× 161 0.3× 128 0.3× 91 1.7k
Gianluca Lazzi United States 31 1.0k 1.0× 429 0.5× 2.8k 4.6× 117 0.2× 2.0k 4.8× 156 4.4k

Countries citing papers authored by Hongbo Jia

Since Specialization
Citations

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

Fields of papers citing papers by Hongbo Jia

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hongbo Jia

This figure shows the co-authorship network connecting the top 25 collaborators of Hongbo Jia. A scholar is included among the top collaborators of Hongbo Jia 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 Hongbo Jia. Hongbo Jia is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Sun, Jingwei, et al.. (2024). Detection of rice panicle density for unmanned harvesters via RP-YOLO. Computers and Electronics in Agriculture. 226. 109371–109371. 14 indexed citations
2.
Liang, Shanshan, et al.. (2024). NeuroSeg-III: efficient neuron segmentation in two-photon Ca2+ imaging data using self-supervised learning. Biomedical Optics Express. 15(5). 2910–2910. 1 indexed citations
3.
4.
Zhang, Zhichun, et al.. (2024). A new stress measurement strategy based on time-frequency characteristics of Lamb waves. Ultrasonics. 142. 107393–107393. 1 indexed citations
5.
Jia, Hongbo, et al.. (2024). Off-axis freeform optical design for large curved field of view imaging. Applied Optics. 63(31). 8152–8152.
6.
Zhou, Jun, et al.. (2023). An adaptive control system for path tracking of crawler combine harvester based on paddy ground conditions identification. Computers and Electronics in Agriculture. 210. 107948–107948. 30 indexed citations
7.
Liang, Shanshan, et al.. (2023). NeuroSeg-II: A deep learning approach for generalized neuron segmentation in two-photon Ca2+ imaging. Frontiers in Cellular Neuroscience. 17. 1127847–1127847. 3 indexed citations
8.
Li, Ruijie, Sibo Wang, Jing Lyu, et al.. (2023). Ten-kilohertz two-photon microscopy imaging of single-cell dendritic activity and hemodynamics in vivo. Neurophotonics. 10(2). 4 indexed citations
9.
He, Chengkang, Qiang Li, Yuanting Cui, et al.. (2022). Recurrent moderate hypoglycemia accelerates the progression of Alzheimer’s disease through impairment of the TRPC6/GLUT3 pathway. JCI Insight. 7(5). 26 indexed citations
10.
Wang, Meng, Ke Liu, Pei Sun, et al.. (2022). Brain-wide projection reconstruction of single functionally defined neurons. Nature Communications. 13(1). 1531–1531. 14 indexed citations
11.
Luo, Liyong, Meng Wang, Shanshan Liang, et al.. (2021). Restoration of Two-Photon Ca2+ Imaging Data Through Model Blind Spatiotemporal Filtering. Frontiers in Neuroscience. 15. 630250–630250. 3 indexed citations
12.
Zhang, Jianxiong, Shanshan Liang, Xiang Liao, et al.. (2021). Non-invasive, opsin-free mid-infrared modulation activates cortical neurons and accelerates associative learning. Nature Communications. 12(1). 2730–2730. 109 indexed citations
13.
Tian, Feng, et al.. (2021). An integrated neural network model for pupil detection and tracking. Soft Computing. 25(15). 10117–10127. 9 indexed citations
14.
Jia, Hongbo, et al.. (2020). EPS: Robust Pupil Edge Points Selection with Haar Feature and Morphological Pixel Patterns. International Journal of Pattern Recognition and Artificial Intelligence. 35(6). 2156002–2156002. 2 indexed citations
15.
Wang, Chanyuan, et al.. (2019). Estimate of Head Posture Based on Coordinate Transformation with MP-MTM-LSTM Network. International Journal of Pattern Recognition and Artificial Intelligence. 34(9). 2059031–2059031. 1 indexed citations
16.
Symvoulidis, Panagiotis, Antonella Lauri, Steffen Schneider, et al.. (2017). NeuBtracker—imaging neurobehavioral dynamics in freely behaving fish. Nature Methods. 14(11). 1079–1082. 25 indexed citations
17.
Yao, Jiwei, Yu Guang, Shanshan Liang, et al.. (2017). Locomotion-Related Population Cortical Ca2+ Transients in Freely Behaving Mice. Frontiers in Neural Circuits. 11. 24–24. 20 indexed citations
18.
Jia, Hongbo, et al.. (2011). Pilot's ground-based spatial disorientation training and its reference values of response. 22(2). 81–85. 1 indexed citations
19.
Jia, Hongbo, et al.. (2010). Effects of instrument visual spatial orientation training of high performance fighter pilots. 21(1). 26–29. 1 indexed citations
20.
Ma, Furong, et al.. (2007). Effects of caloric vestibular stimulation on serotoninergic system in the media vestibular nuclei of guinea pigs. Chinese Medical Journal. 120(2). 120–124. 10 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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