Jin Ye
Scholar

Jin Ye

Google Scholar ID: UFBrJOAAAAAJ
Monash University
Medical AIComputer Vision
Homepage↗Google Scholar↗
Citations & Impact
All-time
Citations
1,777
 
H-index
21
 
i10-index
32
 
Publications
20
 
Co-authors
0
 
Contact
Emaileugene.j.yonng@gmail.comGitHubOpen ↗LinkedInOpen ↗
Publications
3 items
MMBU: A Massive Multi-modal Biomedical Understanding Benchmark to Probe the Perception Capabilities of Vision-Language Models
2026
Cited
0
Single-Rollout Hidden-State Dynamics for Training-Free RLVR Data Selection
2026
Cited
0
SegRap2025: A Benchmark of Gross Tumor Volume and Lymph Node Clinical Target Volume Segmentation for Radiotherapy Planning of Nasopharyngeal Carcinoma
2026
Cited
0
Resume
Academic Achievements
  • 1. One paper accepted by ICCV 2025, focusing on ophthalmic surgical video-language pretraining.
  • 2. Four papers accepted by MICCAI 2025, covering MS lesion segmentation and polyp segmentation.
  • 3. GAIA Workshop accepted at ICCV 2025, exploring the future of generative AI for medical imaging.
  • 4. Two papers accepted by CVPR 2025, about interactive medical image segmentation and SlideChat for gigapixel whole-slide images.
  • 5. FUGC ISBI 2025 Challenge launched, aiming to improve clinical decisions.
  • 6. One paper accepted by NeurIPS 2024, releasing GMAI-MMBench, a comprehensive general medical AI benchmark.
Research Experience
  • Full-time researcher at Shanghai AI Lab, working with Dr. Junjun He and Prof. Yu Qiao; Senior R&D Engineer at Baidu, collaborating with Dr. Xiao Tan and Dr. Wei Zhang.
Education
  • PhD Student, Department of Data Science and AI, Monash University, Supervisors: Prof. Jianfei Cai, A/Prof. Zhaolin Chen, Dr. Bohan Zhuang.
Background
  • Research Interests: Medical AI, particularly medical image segmentation, medical vision-language models, and generative modeling. Aims to translate advanced AI technology into real clinical practice.