I'm a master's student in Fisheries Development, working on computational biology and bioinformatics. I build tools for browsing biological sequences and organizing research workflows.

My master's research is in computational biology, with a focus on comparative genomics, population genetics, and genome assembly and annotation. I have also worked on graph pangenomics, graph representation learning, and single-cell and spatial transcriptomics.

• Genomics — genome assembly and annotation, SNP and structural variation, population differentiation, and evolutionary genomics
• Methods — graph pangenomes, graph representation learning, VGAE-based genotype–phenotype prediction, and multimodal data integration
• Single-cell — scRNA-seq, spatial transcriptomics, and cell composition analysis

• Learning Python and R for data analysis, and building command-line tools
• Plotting mostly with R and ggplot2
• Reading open-source code to learn single-cell and spatial analysis; contributing patches to Squidpy and PyTorch Geometric, and exploring SpatialData
• Learning Rust by building seqviz-rs, a terminal browser for biological data

• seqviz-rs — An interactive terminal browser for FASTA, FASTQ, SAM/BAM, and VCF files, with sequence coloring, quality visualization, and variant inspection. Rust
• SNP-VGAE — Two-stage SNP-VAE + VGAE framework for genomic phenotype prediction with SNP-level attribution. Python PyTorch
• BioAgent-CLI — Natural-language-driven bioinformatics CLI with pipeline automation, a background daemon, and a web dashboard. Python
• sc_cell — Single-cell and spatial transcriptomics analysis of breast cancer data, comparing RCTD and cell2location deconvolution. Python R Jupyter
• GraphPangenomePipeline — Modular graph pangenome pipeline built on cactus, vg, and grannot, from FASTA to annotation and resequencing analysis. Python
• CQ_tools — BWA/samtools/bedtools pipeline for chromosome quotient (CQ) analysis, with static and interactive HTML reports. Python

More projects on GitHub.

• My Website
• Email