Yulei Qin

726 total citations
11 papers, 267 citations indexed

About

Yulei Qin is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Yulei Qin has authored 11 papers receiving a total of 267 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Artificial Intelligence, 4 papers in Radiology, Nuclear Medicine and Imaging and 3 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Yulei Qin's work include COVID-19 diagnosis using AI (4 papers), Lung Cancer Diagnosis and Treatment (3 papers) and Radiomics and Machine Learning in Medical Imaging (2 papers). Yulei Qin is often cited by papers focused on COVID-19 diagnosis using AI (4 papers), Lung Cancer Diagnosis and Treatment (3 papers) and Radiomics and Machine Learning in Medical Imaging (2 papers). Yulei Qin collaborates with scholars based in China, France and United Kingdom. Yulei Qin's co-authors include Jie Yang, Hao Zheng, Xiaolin Huang, Yuemin Zhu, Guang‐Zhong Yang, Yun Gu, Juan Wen, Fangfang Xie, Jiayuan Sun and Feng Yao and has published in prestigious journals such as IEEE Transactions on Medical Imaging, Medical Physics and IEEE Transactions on Neural Networks and Learning Systems.

In The Last Decade

Yulei Qin

10 papers receiving 263 citations

Peers

Yulei Qin

RNMI

PRM

AI

CVPR

GENET

Yaofeng Wen China

Shinji Yamamoto Japan

Lifeng Xu China

Yuefu Zhan China

Jason Causey United States

Stine Hansen Norway

Ahmed Alksas United States

Subrata Bhattacharjee South Korea

Sijuan Huang China

Khushboo Munir Italy

Yaofeng Wen China

Yulei Qin

278 ×2.3

RNMI

82 ×0.9

PRM

135 ×1.9

AI

40 ×0.6

CVPR

16 ×0.3

GENET

Citations per year, relative to Yulei Qin Yulei Qin (= 1×) peers Yaofeng Wen

Countries citing papers authored by Yulei Qin

Since Specialization

Citations

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

Fields of papers citing papers by Yulei Qin

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yulei Qin

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

All Works

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11 of 11 papers shown

1.

Qin, Yulei, et al.. (2025). OPTICAL: Leveraging Optimal Transport for Contribution Allocation in Dataset Distillation. 15245–15254.

2.

Qin, Yulei, et al.. (2025). Multi-Level Optimal Transport for Universal Cross-Tokenizer Knowledge Distillation on Language Models. Proceedings of the AAAI Conference on Artificial Intelligence. 39(22). 23724–23732. 1 indexed citations

3.

Qin, Yulei, Yuting Gao, Zihan Xu, et al.. (2024). SinKD: Sinkhorn Distance Minimization for Knowledge Distillation. IEEE Transactions on Neural Networks and Learning Systems. 36(7). 11887–11901. 1 indexed citations

4.

Qin, Yulei, Xingyu Chen, Chao Chen, et al.. (2023). FoPro: Few-Shot Guided Robust Webly-Supervised Prototypical Learning. Proceedings of the AAAI Conference on Artificial Intelligence. 37(2). 2101–2109. 2 indexed citations

5.

Wang, Jiyue, Yulei Qin, Juan Wen, et al.. (2023). KaryoNet: Chromosome Recognition With End-to-End Combinatorial Optimization Network. IEEE Transactions on Medical Imaging. 42(10). 2899–2911. 7 indexed citations

6.

Zhang, Hanxiao, Liang Chen, Xiao Gu, et al.. (2022). Trustworthy learning with (un)sure annotation for lung nodule diagnosis with CT. Medical Image Analysis. 83. 102627–102627. 12 indexed citations

7.

Zheng, Hao, Yulei Qin, Yun Gu, et al.. (2021). Alleviating Class-Wise Gradient Imbalance for Pulmonary Airway Segmentation. IEEE Transactions on Medical Imaging. 40(9). 2452–2462. 46 indexed citations

8.

Qin, Yulei, Hao Zheng, Yun Gu, et al.. (2021). Learning Tubule-Sensitive CNNs for Pulmonary Airway and Artery-Vein Segmentation in CT. IEEE Transactions on Medical Imaging. 40(6). 1603–1617. 55 indexed citations

9.

Zheng, Hao, Lijun Qian, Yulei Qin, Yun Gu, & Jie Yang. (2020). Improving the slice interaction of 2.5D CNN for automatic pancreas segmentation. Medical Physics. 47(11). 5543–5554. 24 indexed citations

10.

Qin, Yulei, Juan Wen, Hao Zheng, et al.. (2019). Varifocal-Net: A Chromosome Classification Approach Using Deep Convolutional Networks. IEEE Transactions on Medical Imaging. 38(11). 2569–2581. 68 indexed citations

11.

Qin, Yulei, Hao Zheng, Xiaolin Huang, Jie Yang, & Yuemin Zhu. (2018). Pulmonary nodule segmentation with CT sample synthesis using adversarial networks. Medical Physics. 46(3). 1218–1229. 51 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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