Leanne Lai-Hang Chan

519 total citations
28 papers, 394 citations indexed

About

Leanne Lai-Hang Chan is a scholar working on Cellular and Molecular Neuroscience, Cognitive Neuroscience and Computer Vision and Pattern Recognition. According to data from OpenAlex, Leanne Lai-Hang Chan has authored 28 papers receiving a total of 394 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Cellular and Molecular Neuroscience, 9 papers in Cognitive Neuroscience and 7 papers in Computer Vision and Pattern Recognition. Recurrent topics in Leanne Lai-Hang Chan's work include Neuroscience and Neural Engineering (11 papers), Neural dynamics and brain function (7 papers) and Photoreceptor and optogenetics research (6 papers). Leanne Lai-Hang Chan is often cited by papers focused on Neuroscience and Neural Engineering (11 papers), Neural dynamics and brain function (7 papers) and Photoreceptor and optogenetics research (6 papers). Leanne Lai-Hang Chan collaborates with scholars based in Hong Kong, China and United States. Leanne Lai-Hang Chan's co-authors include James D. Weiland, Mark S. Humayun, Hulin Kuang, Hong Yan, Jiajie Chen, Long Chen, Eun Jin Lee, Aaron W. McGee, Henry Shu-Hung Chung and Norberto M. Grzywacz and has published in prestigious journals such as Journal of Neuroscience, Journal of Neurophysiology and IEEE Transactions on Power Electronics.

In The Last Decade

Leanne Lai-Hang Chan

25 papers receiving 390 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Leanne Lai-Hang Chan Hong Kong 11 192 102 97 78 76 28 394
Leanne Lai Hang Chan Hong Kong 14 130 0.7× 107 1.0× 107 1.1× 56 0.7× 140 1.8× 34 504
Albrecht Rothermel Germany 12 321 1.7× 303 3.0× 66 0.7× 111 1.4× 120 1.6× 69 596
Kaijie Wu China 12 87 0.5× 91 0.9× 41 0.4× 33 0.4× 99 1.3× 57 365
G Ranganathan India 8 146 0.8× 33 0.3× 38 0.4× 126 1.6× 83 1.1× 12 419
Cong Shi China 12 86 0.4× 279 2.7× 30 0.3× 71 0.9× 82 1.1× 66 454
Vaishnavi Ranganathan United States 10 72 0.4× 185 1.8× 54 0.6× 43 0.6× 12 0.2× 30 372
Tzai-Wen Chiu Taiwan 10 127 0.7× 48 0.5× 41 0.4× 194 2.5× 8 0.1× 21 506
Anupam Garg United States 13 80 0.4× 19 0.2× 155 1.6× 133 1.7× 113 1.5× 30 604

Countries citing papers authored by Leanne Lai-Hang Chan

Since Specialization
Citations

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

Fields of papers citing papers by Leanne Lai-Hang Chan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Leanne Lai-Hang Chan. 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 Leanne Lai-Hang Chan. The network helps show where Leanne Lai-Hang Chan may publish in the future.

Co-authorship network of co-authors of Leanne Lai-Hang Chan

This figure shows the co-authorship network connecting the top 25 collaborators of Leanne Lai-Hang Chan. A scholar is included among the top collaborators of Leanne Lai-Hang Chan 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 Leanne Lai-Hang Chan. Leanne Lai-Hang Chan 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.
Li, Yongjie, et al.. (2025). Scene adaptation network for visual-thermal urban scene semantic segmentation. Engineering Applications of Artificial Intelligence. 156. 111166–111166.
2.
Yang, Qiushi, et al.. (2025). Progressive Distillation With Optimal Transport for Federated Incomplete Multi-Modal Learning of Brain Tumor Segmentation. IEEE Journal of Biomedical and Health Informatics. 29(5). 3159–3170.
3.
Yang, Kai-Fu, et al.. (2024). Night-Time Vehicle Detection Based on Hierarchical Contextual Information. IEEE Transactions on Intelligent Transportation Systems. 25(10). 14628–14641. 4 indexed citations
4.
Yang, Kai-Fu, et al.. (2024). Self-supervised network for low-light traffic image enhancement based on deep noise and artifacts removal. Computer Vision and Image Understanding. 246. 104063–104063. 3 indexed citations
6.
Chen, Xi, et al.. (2022). Neuromodulation in the developing visual cortex after long-term monocular deprivation. Cerebral Cortex. 33(9). 5636–5645. 2 indexed citations
7.
Chen, Ke, et al.. (2021). Neuronal Oscillatory Signatures in the Developing Mouse Visual Cortex After Short-Term Monocular Deprivation. Cerebral Cortex. 32(12). 2657–2667. 2 indexed citations
8.
Chan, Leanne Lai-Hang, et al.. (2021). ECoG Power Alterations Across Stages of Prolonged Transcorneal Electrical Stimulation in the Blind Mice. 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). 2021. 5784–5787. 2 indexed citations
9.
Chan, Leanne Lai-Hang, et al.. (2020). Spontaneous Feedforward Connectivity in Electrically Stimulated Retinal Degeneration Mice. PubMed. 2020. 3513–3516. 2 indexed citations
10.
Wang, Yi, et al.. (2020). Identification of Retinal Ganglion Cells from β-III Stained Fluorescent Microscopic Images. Journal of Digital Imaging. 33(5). 1352–1363. 2 indexed citations
11.
Cui, Hongyan, et al.. (2019). Electrochemical characteristics of microelectrode designed for electrical stimulation. BioMedical Engineering OnLine. 18(1). 86–86. 19 indexed citations
13.
Yu, Chenyun, et al.. (2018). A fast LSH-based similarity search method for multivariate time series. Information Sciences. 476. 337–356. 22 indexed citations
14.
Li, Guofeng, Wenlong Sheng, Yue Lan, et al.. (2018). Temporal Neuromodulation of Retinal Ganglion Cells by Low-Frequency Focused Ultrasound Stimulation. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 26(5). 969–976. 26 indexed citations
15.
Shu, Lei, et al.. (2017). Unraveling the Morphological Evolution and Etching Kinetics of Porous Silicon Nanowires During Metal-Assisted Chemical Etching. Nanoscale Research Letters. 12(1). 385–385. 26 indexed citations
16.
Kuang, Hulin, et al.. (2016). Combining Region-of-Interest Extraction and Image Enhancement for Nighttime Vehicle Detection. IEEE Intelligent Systems. 31(3). 57–65. 67 indexed citations
17.
Chan, Leanne Lai-Hang, et al.. (2015). An ERP study about the effects of different spatial frequencies and orientations on human brain activity. PubMed. 47. 6202–6205. 2 indexed citations
18.
Chan, Leanne Lai-Hang, et al.. (2014). Plasticity of Binocularity and Visual Acuity Are Differentially Limited by Nogo Receptor. Journal of Neuroscience. 34(35). 11631–11640. 57 indexed citations
19.
Chan, Leanne Lai-Hang, Eun Jin Lee, Mark S. Humayun, & James D. Weiland. (2011). Both electrical stimulation thresholds and SMI-32-immunoreactive retinal ganglion cell density correlate with age in S334ter line 3 rat retina. Journal of Neurophysiology. 105(6). 2687–2697. 43 indexed citations
20.
Ray, Aditi, Gerald J. Sun, Leanne Lai-Hang Chan, et al.. (2010). Morphological alterations in retinal neurons in the S334ter-line3 transgenic rat. Cell and Tissue Research. 339(3). 481–491. 47 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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