CV

Education

• B.S. in biomedical informatics, Zhejiang University, 2022-2026 (expected)
• B.S. in biomedical informatics, University of Edinburgh, 2022-2026 (expeceted)

Experience

• 2023.6 - 2024.2
  • Zhejiang University
  • Indenpedent Undergraduate Project: Identification of specificity bulk T cell receptor sequences in diseases
  • Progress: DONE
  • Supervisor: Professor Wanlu Liu
  • 
• 2024.2 - 2024.5
  • Zhejiang University
  • Assistant Project: Assisting the research of single cell sequencing analysis and spatial transcriptome, especially benchmark of spatial transcriptomics deconvolution methods.
  • Progress: DONE
  • Supervisor: Professor Wanlu Liu
• 2024.5 - 2024.10
  • Zhejiang University
  • Progress: DONE
  • Indenpedent Undergraduate Project: High-resolution Spatial Transcriptomics Database programm, focusing on the most advanced subcellular ST methods.
  • 
• 2024.10 - 2025.1
  • Zhejiang University
  • Progress: DONE
  • Assistant Project: SpatialMETA, A Novel Framework for Integrating Spatial Transcriptomics and Metabolomics Data
  • Supervisor: Professor Wanlu Liu
• 2024.3 -
  • Vanderbilt University
  • Indenpedent Undergraduate Project: Simulation of Spatial Transcriptomics data
  • Progress: Still working on it
  • Supervisor: Professor Maizie Zhou
• 2024.1 -
  • Zhejiang Universitu
  • Independent Undergraduate Project: Spatial T cell receptor sequencing method based on Stereo-seq
  • Progress: Still working on it
  • Supervisor: Professor Wanlu Liu

Skills

• Coding
  • Python
  • Pytorch
  • R
  • SQL
  • JAVA
  • JavaScript
  • Shell
  • Latex
• Biology backgroud
  • Basic biology perspective
  • Interal Medicine
  • Genomics and protomics
  • Immunology
• Specific Techniques
  • Database:
    • Having full exprience in front-end to build a database.
    • Knowing how to plan a well-designed structure.
  • Data analysis:
    • Experience in constructing data analysis pipeline and handling with bulk and sigle cell seqeuncing data.
    • Experience in processing ATAC and ChIP-seq data.
    • Experience in processing spatial transcritomics data
  • Machine learning:
    • Experience in applying ML in multiple tasks, especially: DL tools in spatial transcriptomcis data processing, clustering based on T cell CDR3 animo acid sequences, clustering based on single cell RNA sequencing data, constructing classifiers based on T cell characterisitics. In mathematical modeling competition, learning some basic models in NPL.
    • Understanding basic concepts in pytorch, and finished some toy tasks
• Linux system
  • Advanced Linux user. Mostly working in linux servers in the lab.
  • Managing a small personal Ubuntu machine for daily usage and website construction.

Publications

Two co-author papers under review.