2026 S. Kevin Zhou: Computer Science Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Computer Science	62	2949	2864	402	399	224	13175

Overview

S. Kevin Zhou is affiliated with the University of Science and Technology of China in China. Their research spans multiple intersecting domains including computer science, medicine, and engineering. The main fields of study in their body of work comprise computer science, medicine, and engineering, with significant emphasis on subfields such as radiology, nuclear medicine and imaging, computer vision and pattern recognition, biomedical engineering, artificial intelligence, and electrical and electronic engineering.

The scientist's research topics cover a range of areas critical to medical imaging and analysis. Key topics explored include radiomics and machine learning in medical imaging, medical imaging techniques and applications, advanced X-ray and CT imaging, COVID-19 diagnosis using artificial intelligence, medical imaging and analysis, advanced neural network applications, and medical image segmentation techniques.

Notable recent papers by S. Kevin Zhou include:

Transforming medical imaging with Transformers? A comparative review of key properties, current progresses, and future perspectives (2023, Medical Image Analysis)
Knowledge matters: Chest radiology report generation with general and specific knowledge (2022, Medical Image Analysis)
Rubik's Cube+: A self-supervised feature learning framework for 3D medical image analysis (2020, Medical Image Analysis)
Label-Free Segmentation of COVID-19 Lesions in Lung CT (2021, IEEE Transactions on Medical Imaging)
Deep learning to segment pelvic bones: large-scale CT datasets and baseline models (2021, International Journal of Computer Assisted Radiology and Surgery)

S. Kevin Zhou has collaborated frequently with multiple co-authors, including Heqin Zhu, Fenghe Tang, Qingsong Yao, and Zihang Jiang. These collaborators have contributed considerably to the shared research output, with some publications reflecting close ongoing partnerships.

The scientist's work has appeared repeatedly in key publication venues, predominantly in arXiv (Cornell University), Medical Image Analysis, IEEE Transactions on Medical Imaging, Lecture Notes in Computer Science, and npj Digital Medicine. The distribution of publications indicates a strong presence in both open-access preprints and peer-reviewed journals specialized in medical imaging and computer science.

Beyond journal articles, S. Kevin Zhou has contributed to book publications with Springer Science+Business Media, featuring in volumes related to Medical Image Computing and Computer Assisted Intervention presented at MICCAI 2020.

Best Publications

A Review of Deep Learning in Medical Imaging: Imaging Traits, Technology Trends, Case Studies With Progress Highlights, and Future Promises

S. Kevin Zhou;Hayit Greenspan;Christos Davatzikos;James S. Duncan

1545
Citations
Visual tracking and recognition using appearance-adaptive models in particle filters

Shaohua Kevin Zhou;R. Chellappa;B. Moghaddam

970
Citations
FaceNet2ExpNet: Regularizing a Deep Face Recognition Net for Expression Recognition

Hui Ding;Shaohua Kevin Zhou;Rama Chellappa

442
Citations
Probabilistic recognition of human faces from video

Shaohua Zhou;Volker Krueger;Rama Chellappa

389
Citations
Combo loss: Handling input and output imbalance in multi-organ segmentation

Saeid Asgari Taghanaki;Saeid Asgari Taghanaki;Yefeng Zheng;S. Kevin Zhou;Bogdan Georgescu

372
Citations
Shallow Attention Network for Polyp Segmentation.

Jun Wei;Yiwen Hu;Yiwen Hu;Ruimao Zhang;Zhen Li

325
Citations
From sample similarity to ensemble similarity: probabilistic distance measures in reproducing kernel Hilbert space

S.K. Zhou;R. Chellappa

245
Citations
Deep Learning for Medical Image Analysis

S. Kevin Zhou;Hayit Greenspan;Dinggang Shen

222
Citations
Learning to Prune Filters in Convolutional Neural Networks

Qiangui Huang;Kevin Zhou;Suya You;Ulrich Neumann

208
Citations
Automatic Liver Segmentation Using an Adversarial Image-to-Image Network

Dong Yang;Daguang Xu;S. Kevin Zhou;Bogdan Georgescu

199
Citations
Hierarchical, learning-based automatic liver segmentation

Haibin Ling;S.K. Zhou;Yefeng Zheng;B. Georgescu

197
Citations
Deep reinforcement learning in medical imaging: A literature review

S. Kevin Zhou;T. Hoang Ngan Le;Khoa Luu;Hien Van Nguyen

193
Citations
Automatic Liver Segmentation Using Adversarial Image-to-Image Network

Dong Yang;Daguang Xu;Shaohua Kevin Zhou;Bogdan Georgescu

182
Citations
ADN: Artifact Disentanglement Network for Unsupervised Metal Artifact Reduction

Haofu Liao;Wei-An Lin;S. Kevin Zhou;Jiebo Luo

175
Citations
Hierarchical Parsing and Semantic Navigation of Full Body CT Data

Sascha Seifert;Adrian Barbu;S. Kevin Zhou;David Liu

172
Citations
DuDoRNet: Learning a Dual-Domain Recurrent Network for Fast MRI Reconstruction With Deep T1 Prior

Bo Zhou;S. Kevin Zhou

166
Citations
Image based regression using boosting method

Shaohua Kevin Zhou;B. Georgescu;Xiang Sean Zhou;D. Comaniciu

163
Citations
Dual-GAN: Joint BVP and Noise Modeling for Remote Physiological Measurement

Hao Lu;Hu Han;S. Kevin Zhou

163
Citations
Artifact Disentanglement Network for Unsupervised Metal Artifact Reduction

Haofu Liao;Wei-An Lin;Jianbo Yuan;S. Kevin Zhou

161
Citations
Rubik's Cube+: A self-supervised feature learning framework for 3D medical image analysis.

Jiuwen Zhu;Yuexiang Li;Yifan Hu;Kai Ma

159
Citations
Appearance Characterization of Linear Lambertian Objects, Generalized Photometric Stereo, and Illumination-Invariant Face Recognition

S.K. Zhou;G. Aggarwal;R. Chellappa;D.W. Jacobs

148
Citations
Spine detection in CT and MR using iterated marginal space learning

B. Michael Kelm;Michael Wels;S. Kevin Zhou;Sascha Seifert

141
Citations
3D Anisotropic Hybrid Network: Transferring Convolutional Features from 2D Images to 3D Anisotropic Volumes

Siqi Liu;Daguang Xu;S. Kevin Zhou;Thomas Mertelmeier

97
Citations

Frequent Co-Authors

Dorin Comaniciu Siemens (United States)

Yefeng Zheng Tencent (China)

Hu Han Chinese Academy of Sciences

Daguang Xu Nvidia (United Kingdom)

Jiebo Luo University of Rochester

Bogdan Georgescu Princeton University

James S. Duncan Yale University

Joachim Hornegger University of Erlangen-Nuremberg

Rama Chellappa Johns Hopkins University

Ghassan Hamarneh Simon Fraser University

External Links

Personal website of S. Kevin Zhou

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