Xiaowei Xu
Scholar

Xiaowei Xu

Google Scholar ID: 1vVgUeQAAAAJ
Guangdong Provincial People's Hospital
Deep learningMedical Image segmentationAutomatic diagnosisCardiovascular disease
Citations & Impact
All-time
Citations
3,020
 
H-index
27
 
i10-index
52
 
Publications
20
 
Co-authors
8
list available
Publications
20 items
Browse publications on Google Scholar (top-right) ↗
Resume (English only)
Academic Achievements
  • Published papers in top-tier venues: CVPR, AAAI, MICCAI, MIDL, ISBI, DAC, ICCAD
  • Published in top journals: TPAMI, MIA, TMI, TCAD, TBioCAS, Nature Electronics, Nature Machine Intelligence
  • Paper accepted by Medical Image Analysis (IF=10.7), Feb 2025
  • Paper accepted by Expert Systems with Applications (IF=7.5), Dec 2024
  • Paper accepted by Pattern Recognition (IF=7.5), Dec 2024
  • Paper accepted by ECCV (top CV conference), July 2024
  • Paper accepted by MICCAI (top medical imaging conference), June 2024
  • Paper accepted by IEEE TNNLS (IF=10), Dec 2023
  • Granted Guangzhou Science and Technology Project (1M CNY), May 2025
  • Appointed Associate Editor of Pattern Recognition (IF=7.5), Feb 2025
  • Appointed Associate Editor of International Journal of Cardiovascular Imaging, Jan 2025
Background
  • Associate Professor at Guangdong Cardiovascular Institute (ranked top 3-4 in cardiovascular specialty in China), Guangdong Provincial People's Hospital (ranked top 27 in China)
  • Co-director of the Laboratory of Artificial Intelligence and 3D Technologies for Cardiovascular Diseases; lab director is Jian Zhuang, former dean of the hospital
  • Research focuses on AI for cardiovascular diseases, including deep learning and medical image processing
  • Team applies deep learning to clinical applications in cardiovascular diseases and collects large-scale medical data from the hospital
  • Strong commitment to open-source research: published 10+ datasets and code repositories on Kaggle
  • Currently recruiting professors (assistant/associate/full), postdoctoral fellows, and research assistants in medical image analysis