Zi Yang

1.6k total citations · 1 hit paper
34 papers, 1.1k citations indexed

About

Zi Yang is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition and Artificial Intelligence. According to data from OpenAlex, Zi Yang has authored 34 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Radiology, Nuclear Medicine and Imaging, 9 papers in Computer Vision and Pattern Recognition and 7 papers in Artificial Intelligence. Recurrent topics in Zi Yang's work include Advanced Radiotherapy Techniques (5 papers), Radiomics and Machine Learning in Medical Imaging (5 papers) and Complex Network Analysis Techniques (5 papers). Zi Yang is often cited by papers focused on Advanced Radiotherapy Techniques (5 papers), Radiomics and Machine Learning in Medical Imaging (5 papers) and Complex Network Analysis Techniques (5 papers). Zi Yang collaborates with scholars based in China, United States and Hong Kong. Zi Yang's co-authors include Chi Wang, Jie Tang, Jimeng Sun, Jie Tang, Zhong Su, Keke Cai, Juanzi Li, Li Zhang, Li Zhang and Xuejun Gu and has published in prestigious journals such as SHILAP Revista de lepidopterología, International Journal of Radiation Oncology*Biology*Physics and Optics Express.

In The Last Decade

Zi Yang

30 papers receiving 1.0k citations

Hit Papers

Social influence analysis in large-scale networks 2009 2026 2014 2020 2009 200 400 600
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.

  1. Social influence analysis in large-scale networks
    2009 616 citations Zi Yang et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Zi Yang China 13 600 444 288 128 120 34 1.1k
Reza Bosagh Zadeh United States 12 165 0.3× 277 0.6× 209 0.7× 60 0.5× 165 1.4× 17 757
Asgarali Bouyer Iran 22 736 1.2× 468 1.1× 205 0.7× 96 0.8× 91 0.8× 85 1.3k
Amir Sheikhahmadi Iran 16 864 1.4× 303 0.7× 143 0.5× 194 1.5× 60 0.5× 40 1.2k
Amit Goyal India 10 671 1.1× 212 0.5× 268 0.9× 137 1.1× 50 0.4× 27 1.0k
Mark Goldberg United States 17 273 0.5× 241 0.5× 148 0.5× 141 1.1× 64 0.5× 53 994
Tianyi Wang China 16 113 0.2× 368 0.8× 234 0.8× 164 1.3× 322 2.7× 59 1.0k
Kaize Ding United States 17 173 0.3× 924 2.1× 335 1.2× 134 1.0× 134 1.1× 56 1.1k
Masoud Asadpour Iran 15 381 0.6× 391 0.9× 157 0.5× 123 1.0× 38 0.3× 61 841
Erheng Zhong Hong Kong 18 137 0.2× 587 1.3× 372 1.3× 71 0.6× 293 2.4× 28 1.1k
Liang Gou United States 18 294 0.5× 709 1.6× 242 0.8× 115 0.9× 435 3.6× 43 1.2k

Countries citing papers authored by Zi Yang

Since Specialization
Citations

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

Fields of papers citing papers by Zi Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zi Yang

This figure shows the co-authorship network connecting the top 25 collaborators of Zi Yang. A scholar is included among the top collaborators of Zi Yang 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 Zi Yang. Zi Yang 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
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Adam, Kirsten, Zi Yang, & John T. Serences. (2024). First encounters: Estimating the initial magnitude of attentional capture. Visual Cognition. 32(9-10). 822–844. 2 indexed citations
4.
Fu, Jie, Zi Yang, Stavros Melemenidis, et al.. (2024). Exploring Deep Learning for Estimating the Isoeffective Dose of FLASH Irradiation From Mouse Intestinal Histological Images. International Journal of Radiation Oncology*Biology*Physics. 119(3). 1001–1010. 4 indexed citations
5.
Yang, Zi, Neelan J. Marianayagam, Jae‐Hyun Park, et al.. (2024). Deep learning-based overall survival prediction in patients with glioblastoma: An automatic end-to-end workflow using pre-resection basic structural multiparametric MRIs. Computers in Biology and Medicine. 185. 109436–109436. 1 indexed citations
6.
Yang, Zi, et al.. (2023). Leveraging global binary masks for structure segmentation in medical images. Physics in Medicine and Biology. 68(18). 185023–185023.
7.
Kang, Jia‐Lin, et al.. (2023). Sequence-to-sequence digital twin model in chemical plants with internal rolling training algorithm. Applied Soft Computing. 146. 110608–110608. 5 indexed citations
8.
Yang, Zi, Asal Rahimi, Nathan Kim, et al.. (2023). A deep learning approach for automatic delineation of clinical target volume in stereotactic partial breast irradiation (S-PBI). Physics in Medicine and Biology. 68(10). 105011–105011. 7 indexed citations
9.
Yang, Zi, Lin Ma, Strahinja Stojadinović, et al.. (2022). Ensemble learning for glioma patients overall survival prediction using pre-operative MRIs. Physics in Medicine and Biology. 67(24). 245002–245002. 2 indexed citations
10.
Yang, Zi, Lin Ma, Strahinja Stojadinović, et al.. (2021). Deep-learning and radiomics ensemble classifier for false positive reduction in brain metastases segmentation. Physics in Medicine and Biology. 67(2). 25004–25004. 16 indexed citations
11.
Sun, Rui, et al.. (2021). Visible-Infrared Person Re-Identification Based on Frequency-Domain Simulated Multispectral Modality for Dual-Mode Cameras. IEEE Sensors Journal. 22(1). 989–1002. 14 indexed citations
12.
Yang, Zi, et al.. (2021). Dose kernel decomposition for spot‐based radiotherapy treatment planning. Medical Physics. 49(2). 1196–1208. 1 indexed citations
13.
Lin, Zi, Jeremiah Zhe Liu, Zi Yang, Nan Hua, & Dan Roth. (2020). Pruning Redundant Mappings in Transformer Models via Spectral-Normalized Identity Prior. 719–730. 18 indexed citations
14.
Yang, Zi, et al.. (2020). Motion robust 4D-MRI sorting based on anatomic feature matching: A digital phantom simulation study. SHILAP Revista de lepidopterología. 1(1). 41–47. 2 indexed citations
15.
Yu, Shaode, Erlei Zhang, Hang Yu, et al.. (2020). Robustness study of noisy annotation in deep learning based medical image segmentation. Physics in Medicine and Biology. 65(17). 175007–175007. 30 indexed citations
16.
Yang, Zi, Yan Liu, Strahinja Stojadinović, et al.. (2020). A web‐based brain metastases segmentation and labeling platform for stereotactic radiosurgery. Medical Physics. 47(8). 3263–3276. 13 indexed citations
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Yang, Zi, et al.. (2010). Social Community Analysis via a Factor Graph Model. IEEE Intelligent Systems. 26(3). 58–65. 12 indexed citations
20.
Tang, Jie, Jing Zhang, Jeffrey Xu Yu, et al.. (2009). Topic Distributions over Links on Web. 3. 1010–1015. 7 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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