CV

Education

• M.S. in Medical Imaging Technology (医学影像技术, academic master’s)
  • Shanghai Jiao Tong University (上海交通大学), School of Medical Technology, Sep 2025 - Jun 2028
• B.E. in Biomedical Engineering (生物医学工程)
  • Beihang University (北京航空航天大学), School of Biomedical Engineering, Sep 2021 - Jun 2025

Research Interests

• AI4Healthcare (AI for Healthcare)
• Representation learning
• 3D perception algorithms
• Medical image analysis and spatial understanding

Industry Experience

• Algorithm Intern, Momenta — Autonomous Driving
  • Oct 2025 - Dec 2025
  • Adapted BEVFormer inference and evaluation entry points for road-scene 3D detection; designed data audits, calibration-projection checks, and scenario-based analysis workflows.
  • Defined timestamp indexing, cache-reset procedures, and regression checks for abnormal temporal-history updates.
  • Standardized traceability across configurations, logs, and predictions for reproducible perception evaluation and engineering handoff.

Research Experience

• Research Intern, BGI Research Institute (华大研究院), Beijing, China
  • Jun 2024 - Nov 2024
  • Worked on statistical analysis, spatial processing, region annotation, and image segmentation for high-resolution spatiotemporal tissue datasets.
  • Applied Python, R, Seurat, ImageJ, QuPath, and spatial transcriptomics toolkits in research workflows.

Skills

• Programming: Python, C#, Bash, Git, HTML, Markdown
• Machine learning: PyTorch, scikit-learn, OpenCV, NumPy, Hugging Face
• Research tools: Jekyll, GitHub Pages, LaTeX, ImageJ, QuPath
• Languages: Mandarin Chinese (native), English

Selected Publications

VQPET: Leveraging Vector-Quantized Codebook Prior for PET Image Synthesis

H. Chen, Z. Yang, Y. Zhou, X. Zhang, H. Zhang, D. Zhao, B. Wei, G. Zhou, and Y. Xu. (2026). "VQPET: Leveraging Vector-Quantized Codebook Prior for PET Image Synthesis." IEEE Transactions on Medical Imaging, 45(5), 2542–2560.

MoMIL: Multi-order Enhanced Multiple Instance Learning for Computational Pathology

Yuqi Zhang, Xiaoqian Zhang, Jiakai Wang, Baoyu Liang, Yuancheng Yang, and Chao Tong. (2026). "MoMIL: Multi-order Enhanced Multiple Instance Learning for Computational Pathology." Image and Vision Computing, 167, 105918.

Research Progress and Clinical Translation of Photoacoustic–Ultrasound Fusion Imaging in Breast Cancer Diagnosis and Therapy

Xiaoqian Zhang, Jingwen Zhang, Yijie Dong, and Jianqiao Zhou. (2025). "Research Progress and Clinical Translation of Photoacoustic–Ultrasound Fusion Imaging in Breast Cancer Diagnosis and Therapy." Advanced Ultrasound in Diagnosis and Therapy, 9(4), 467–482.

多模态基础模型与超声影像的交叉应用

孟雅清, 杨景涵, 李欣玥, 张啸谦, 田捷, 王坤. (2025). "多模态基础模型与超声影像的交叉应用." 中华医学超声杂志（电子版）, 22(08), 777-782.

Mamba2MIL: State Space Duality Based Multiple Instance Learning for Computational Pathology

Yuqi Zhang, Xiaoqian Zhang, Jiakai Wang, Yuancheng Yang, Taiying Peng, and Chao Tong. (2024). "Mamba2MIL: State Space Duality Based Multiple Instance Learning for Computational Pathology." arXiv preprint arXiv:2408.15032.

Honors and Awards

• Second Prize, Academic Excellence Scholarship, Beihang University, 2021-2022
• Third Prize, 8th National Academic English Vocabulary Competition for College Students, 2023
• Excellent Scientific Research Achievement, BUAA Scientific Research Class, Fall 2022
• Third Prize, 2024 National Biomedical Engineering Innovation Competition for College Students

Profiles

• Google Scholar: https://scholar.google.co.jp/citations?user=maQlQdIAAAAJ&hl=zh-CN
• ORCID: https://orcid.org/0009-0004-5587-2188
• GitHub: https://github.com/Xiaoqian-Zhang-Shawno