Computational Biologist & Bioinformatics Data Engineer · PhD, Genetics, Genomics & Development · Cornell University
Building scientific data infrastructure that informs rare disease drug decisions at Alexion (AstraZeneca) · Boston, MA
Expert across the full NGS spectrum — bulk, single-cell, spatial, and long-read — typed, tested, and deployed at scale.
As a Bioinformatics Data Engineer, I architect and operate the cloud genomics platform combining AWS, HPC, Seqera/Nextflow Tower, Databricks, and Quilt. I support a 10-member bioinformatics & AI/ML group. I design and deliver end-to-end NGS pipelines and regulatory-grade analytical reports that directly inform go/no-go decisions across rare disease genomic medicine programs, covering the full assay spectrum: bulk and single-cell RNA-Seq, scATAC-Seq, spatial transcriptomics, long-read sequencing, isoform assembly, custom library design, and UMI-aware workflows.
A flagship project: a FAIR metadata-powered genomic data catalog built on Quilt.bio, enhanced with a custom pydantic_ai metadata extraction workflow to enabling unlimited-scale rare-disease discovery across Alexion's existing sequencing corpus.
- sirnaforge — Multi-species siRNA/miRNA design toolkit with NGS workflow integration, ViennaRNA thermodynamic scoring, and comprehensive off-target prediction
- quiltdata/quilt (contributor) — Active collaborator on the Quilt data catalog. Integrate feedback from users and suggest enhancements that benefit all. Open source science.
- NC_Timecourse — Reproducible R analysis pipeline for the neural crest epigenomics study underlying the Dev. Cell 2022 publication
RNA-Seq · scRNA-Seq · scATAC-Seq · Spatial Transcriptomics · Long-Read / Nanopore / PacBio / Iso-Seq · Isoform Assembly · CRISPR / Gene Editing · siRNA & ASO Off-Target · ChIP-Seq / CUT&RUN / CUT&TAG · Hi-C · MPRA · UMI-aware workflows · nf-core
Core languages
Infrastructure & pipelines
Python ecosystem
AI & ML
