About
Yunhao Li
PhD student at The Hong Kong Polytechnic University, specializing in Medical Image Analysis, Computer Vision, and trustworthy AI with peer-reviewed work on reliable clinical imaging.
My research centers on Computer Vision, Medical Image Analysis, and Multimodal Learning, with an emphasis on dependable methods for clinical decision support. I aim to translate algorithmic advances into measurable contributions for medical science and human health.
Publications
SegTom: A 3D Volumetric Medical Image Segmentation Framework for Thoracoabdominal Multi-Organ Anatomical Structures
Yan Pang, Yunhao Li , Jiaming Liang, Hao Chen, Ying Hu, Qiong Wang.
Efficient Breast Lesion Segmentation from Ultrasound Videos Across Multiple Source-limited Platforms
Yan Pang, Yunhao Li , Teng Huang, Jiaming Liang, Ziyu Ding, Hao Chen, Baoliang Zhao, Ying Hu, Zheng Zhang, Qiong Wang.
Online Self-distillation and Self-modeling for 3D Brain Tumor Segmentation
Yan Pang, Yunhao Li , Teng Huang, Jiaming Liang, Zhen Wang, Changyu Dong, Dongyang Kuang, Ying Hu, Hao Chen, Tim Lei, Qiong Wang.
Optimized Breast Lesion Segmentation in Ultrasound Videos Across Varied Resource-Scant Environments
Yunhao Li , Chen Zibin, Yan Junming, Ding Ziyu, Li Jie ,Pei Xiaoqing, Zhang Zheng, Qiong Wang, Yan Pang.
IPM: An Intelligent Component for 3D Brain Tumor Segmentation Integrating Semantic Extractor and Pixel Refiner
Yunhao Li , Caiyan Tan, Mingdu Zhang, Xi Zhang, Teng Huang ,Xiao-Qing Pei, Yan Pang.
Slim UNETR: Scale hybrid transformers to efficient 3D medical image segmentation under limited computational resources
Yan Pang, Jiaming Liang, Teng Huang, Hao Chen, Yunhao Li , Dan Li, Lin Huang, Qiong Wang.
CAM-PC: A novel method for camouflaging point clouds to counter adversarial deception in remote sensing
Bo Wei, Teng Huang, Xi Zhang, Jiaming Liang, Yunhao Li , Cong Cao, Dan Li, Yongfeng Chen, Huagang Xiong, Feng Jiang, Xiqiu Zhang.
AgileNet: A Rapid and Efficient Breast Lesion Segmentation Method for Medical Image Analysis
Jiaming Liang, Teng Huang, Dan Li, Ziyu Ding, Yunhao Li , Lin Huang, Qiong Wang, Xi Zhang.
Programming Skills
Full-stack delivery across research prototypes and production systems, with a focus on reliable ML, developer experience, and thoughtful tooling choices.
AI & Data
Train and fine-tune CV/LLM models, ship evaluation loops, and keep datasets reproducible.
Backend & Services
Design APIs and async pipelines with observability, caching, and resource-aware deployment.
System Glue
Bridge research and product: prompt tooling, feature flags, and rollouts tied to metrics.
Collaboration
Mentor teams, write docs, and keep coding standards consistent for safer shipping.
How I build
Practical workflows that keep experiments measurable and services shippable.
- •Start with measurable prototypes, then instrument tracing/metrics before scaling models or infra.
- •Prefer lightweight adapters, retrieval, and dataset curation over brute-force training.
- •Ship services with automated testing, containerization, and staged rollout paths for resilience.
CI/CD pipelines with containerized services, feature flags for safe rollout, and dashboards to watch model drift.
Collaborating with the community to strengthen LLM and CV tooling.
Education
Work Experience
ML Researcher & Data Analyst
China Post Bank
- Developed AI-driven finance data precision recommendation model for customer marketing.
- Designed and implemented a model training engine for automatic rolling training and optimization
- Contributed to a 15% increase in performance for China Post Bank GuangZhou.
