Experiences
SpatialTCR: An integrated platform for high-resolution spatial sequencing of T cell receptor repertoires
ZJU-UoE Institute, Zhejiang University, Mentor: Prof. Wanlu Liu
2025-04 – Present
- Developed a high-resolution spatial TCR profiling method leveraging Stereo-seq, enabling accurate reconstruction of TCR alpha and beta chains directly from tissue sections.
- Created a dedicated computational pipeline for reliable chain pairing, clonotype mapping, and integration with spatial transcriptomic data.
- Applied the platform to human tissues, revealing spatial T cell clonotype distributions and immune microenvironments with high confidence.
EasyLAMP: Advanced LAMP Primer Design Model
ZJU-UoE Institute, Zhejiang University, Mentor: Dr. Hugo C. Sámano-Sánchez
2025-02 – Present
- Developed a LAMP primer design tool based on comprehensive threshold screening of primer characteristics.
- Built a predictive model using extensive LAMP experimental data to evaluate primer performance and forecast amplification success under various conditions.
SpatialMETA: A Novel Framework for Integrating Spatial Transcriptomics and Metabolomics Data
ZJU-UoE Institute, Zhejiang University, Mentor: Prof. Wanlu Liu
2024-09 – 2025-04
- Conducted large-scale benchmarking of 7 integration methods (spaVAE, scVI, scPoli, …) across 6 multi-batch spatial transcriptomic-metabolomic datasets.
- Developed quantitative batch integration assessment system:
- Basic ST assessment (Continuity (CHAOS, PAS, …), Marker score (Moran’s, Geary’s, …), Specificity score (Specificity, Logistic regression, …)
- Biological conservation (ASW, Cell-type LISI (cLISI), …)
- Batch correction (Batch ASW, Integration LISI (iLISI), …)
- Reconstruction fidelity (Cosine Similarity, Pearson Correlation)
HDSTdb: High-definition Spatial Transcriptomics Database
ZJU-UoE Institute, Zhejiang University, Mentor: Prof. Wanlu Liu
2024-04 – 2024-09
- Analyzed 246 healthy and diseased samples from three subcellular-level spatial transcriptomic sequencing platforms: Visium HD, Stereo-seq, and Xenium.
- Developed an interactive, multi-resolution visualization tool (e.g., 8µm, 16µm bins for Visium HD) with adjustable leiden clustering and differential gene expression (DEG) analysis.
- Enabled visualization of cell segmentation with advanced analyses, including cell shape characterization, spatial distribution, and cell-cell interactions.
Disease-Specific TCR Identification from Bulk TCR Sequencing Data
ZJU-UoE Institute, Zhejiang University, Mentor: Prof. Wanlu Liu
2023-04 – 2024-04
- Processed and analyzed multi-disease bulk TCR datasets comprising 465.8M human TCR entries, including 330.3M from 59 NCBI projects and 135.5M from 66 immuneACCESS projects, enabling comprehensive TCR repertoire analysis.
- Developed a disease-specific recognition framework utilizing unsupervised learning methodologies with the GIANA tool, enhancing TCR classification accuracy.