Skip to main content

Core Domains

Generative AI & Diffusion Models

  • Diffusion models (DDPM, DDIM, diffusion transformers)
  • Time-series generation (e.g., DiffWave-style models for FHR / UC)
  • GANs for medical and signal data (Pix2Pix, CycleGAN)
  • Synthetic data & augmentation for imbalanced clinical datasets
Generative AI & Diffusion Models

Computer Vision & Medical Imaging

  • U-Net / ResNet / ViT-style models for segmentation and classification
  • Medical imaging analysis (CT, MRI, X-ray, ultrasound)
  • CTG / FHR signal representation and weakly supervised learning
  • Multi-task models for lesion detection, segmentation, and report generation
Computer Vision & Medical Imaging

RAG, NLP & Knowledge-Enhanced AI

  • Graph RAG pipelines over clinical knowledge bases
  • Neo4j knowledge graphs and retrieval tuning
  • LLMs (Qwen, LLaMA, Gemma) for medical language tasks
  • LangChain / LlamaIndex & prompt engineering for MedAI workflows
RAG, NLP & Knowledge-Enhanced AI

Selected Publications

  • Li, Xiaoqing, Lu, Y., & Fu, X. (2021). Building the Internet of Things platform for smart maternal healthcare services with wearable devices and cloud computing. Future Generation Computer Systems, 118, 282–296.
  • Li, Xiaoqing, Lu, Y., Ngiam, K. Y., Yu, Z., & Furqan, M. S. (2024). FHRDiff: Leveraging Diffusion Models for Conditional Fetal Heart Rate Signal Generation. IEEE BIBM 2024, 2148–2155.
  • Li, Xiaoqing, Cai, P., Lu, Y., Shi, S., Ma, L., & Fu, X. (2025). CTGDiff: A Conditional Diffusion Model for Cardiotocography Signal Synthesis. ICASSP 2025, 1–5.
  • Li, Xiaoqing, Lu, Y., Shi, S., Zhu, X., & Fu, X. (2021). The impact of healthcare monitoring technologies for better pregnancy. IEEE ICET 2021, 731–736.
  • Lu, Y., Zhang, X., Jing, L., Li, Xiaoqing, & Fu, X. (2020). Estimation of the foetal heart rate baseline based on singular spectrum analysis and empirical mode decomposition. Future Generation Computer Systems, 112, 126–135.
  • Lu, Y., Fu, X., Li, Xiaoqing, & Qi, Y. (2020). Cardiac chamber segmentation using deep learning on magnetic resonance images from patients before and after atrial septal occlusion surgery. IEEE EMBC 2020, 1211–1216.
  • Zhu, X., Shi, S., Li, Xiaoqing, & Lu, Y. (2021). Charging Route Planning for Wireless Rechargeable Sensor Networks. IEEE ICET 2021, 1089–1094.
  • Xu, Z., Li, Xiaoqing, Lu, Y., Zhang, W., Shi, S., & Fu, X. (2025). Multi-Task Self-Supervised Learning for Automated Measurement of Left Ventricular Ejection Fraction in Echocardiography. IEEE ICME 2025.
  • Feng, W., Li, Xiaoqing, Lu, Y., Shi, S., & Qi, Y. (2025). MambaXray-CTL: Multi-Stage Contrastive Training for Medical Report Generation with a Mamba-Based Multi-Modal Large Model. IEEE SMC 2025.

Awards & Honors

  • Outstanding Graduate of Shenzhen University, Jul 2022.
  • “The Star of the Craftsman” Scholarship – 1st Prize (2019 & 2021), 2nd Prize (2020).
  • “Research and Innovation” Scholarship – 1st Prize, Nov 2021.
  • High-Level Paper Award (Natural Science) – 1st Prize, Oct 2021.
  • 3rd Prize, “Creating Youth” China College Students Entrepreneurship Competition (Provincial Level), Jul 2020.
  • 3rd Prize, Asia and Pacific Mathematical Contest in Modeling, Jan 2021.