Welcome

I'm a Data Analyst and Computational Researcher with a passion for using data to drive insights in neuroimaging, biomedical image analysis, and machine learning. With a Master’s in Data Science from Vanderbilt University and over five years of experience, I specialize in building scalable data pipelines, analyzing high-dimensional data, and applying advanced ML techniques to real-world problems.

📍 San Francisco, CA
📫 Email me | LinkedIn | GitHub

Xueyuan Li

🧪 Current Role

Staff Research Associate II
University of California, San Francisco
📍 San Francisco, CA | 🗓 Jan 2025 – Present

Working in the labs of Dr. Janine Lupo and Dr. Tony Yang, focusing on cutting-edge neuroimaging research. Responsible for collecting, transferring, processing, and analyzing MRI and EEG data from patients to advance understanding in biomedical imaging and develop innovative imaging techniques.

🎓 Education

M.S. in Data Science
Vanderbilt University, Nashville, USA
🗓 Aug 2022 – May 2024
Relevant Coursework: Python & R, Statistics, Machine Learning, Medical Image Analysis, Database Systems, Cloud Computing, Big Data Scaling

B.E. in Data Science and Big Data Technology
Henan University, Henan, China
🗓 Sep 2018 – Jun 2022
Relevant Coursework: Data Structures, Operating System, Computer Network, Programming, Big Data Platforms, Algorithms, AI

🔬 Research Highlights

Biomedical Image Analysis (Vanderbilt University HRLB Lab) 🗓 May 2023 – Oct 2024

  • Specialized in high-dimensional data analysis and computational pathology, focusing on advancing machine learning and deep learning algorithms for high-resolution biomedical imaging.
  • Developed the SAM-assisted Molecular-empowered Learning approach, leveraging innovative techniques to improve segmentation accuracy and enhance model robustness in biomedical image analysis.

HRLB Lab

📚 Publications

  • Xueyuan Li, Ruining Deng, Yucheng Tang, Shunxing Bao, Haichun Yang, Yuankai Huo.
    Leverage Weakly Annotation to Pixel-wise Annotation via Zero-shot Segment Anything Model for Molecular-empowered Learning.
    SPIE Medical Imaging Conferences, 2024
    🏆 Finalist, Robert F. Wagner All-Conference Best Student Paper Award
    Read on arXiv

💻 Technical Skills

  • Languages: Python, R, SQL, Java, C++
  • Tools: Jupyter, RStudio, 3D-Slicer, ITK/VTK
  • Cloud & Database: AWS, GCP, MySQL
  • Specialties: fMRI & EEG analysis, ML & DL models, image segmentation, pipeline automation

Thanks for visiting! Feel free to explore my GitHub projects or get in touch.