# resume
Samuel Bharti
Computational biologist · apps, packages, and workflows for omics data
Birmingham, AL
samuelbharti.io@gmail.comsamuelbharti.comgithub.com/samuelbhartilinkedin.com/in/samuelbhartiorcid.org/0000-0003-4190-7058
Summary
I'm a PhD candidate in biomedical engineering and bioinformatics at the University of Alabama at Birmingham, where I own the multi-omics analysis of Neurofibromatosis Type 1 (NF1) tumor models from quality control through to the drug shortlist. I also own six open-source packages for omics data in R, Python, and TypeScript. The apps I build on them run on research infrastructure, in the hands of the scientists who generated the data.
Skills
all of them →- languages
- R, Python, SQL, TypeScript, JavaScript, Bash, Git, GitHub
- data products
- R Shiny, Quarto, ggplot2, Plotly, D3
- bioinformatics
- single-cell & spatial transcriptomics, bulk RNA-seq, multi-omics integration, Seurat, DESeq2, nf-core / Nextflow
- infrastructure
- reproducible workflows, Docker, AWS, GCP, HPC / SLURM
- agentic AI
- agent systems, tool calling, MCP, LLM apps, machine learning
Experience
- Own the single-nuclei and multi-omics analysis of NF1-associated tumor models, from quality control to the shortlist of drugs worth testing.
- Built and deployed 5+ Shiny applications and internal tools on UAB research infrastructure for visualization, sample tracking, QC review, and multi-omics exploration.
- Caught sample contamination in 3′ datasets that quality control had passed, and had it confirmed by the platform vendor.
- Owned five packages end to end, from API design through release: biobouncer, biohttp, bioclients, biocohort, and plotomics.
- Contributed seven merged pull requests upstream to the Shiny ecosystem, and the first shinyreact release credits me as a New Contributor.
- Built more than ten apps across R, Python, and JavaScript, mostly for computational biology and bioinformatics.
- Built MOLV, a Shiny platform and R package for locus-first visualization across 11,000+ GWAS, eQTL, pQTL, single-cell, and ATAC-seq datasets in Alzheimer's disease.
- Built its components and workflows so the same locus view worked across every dataset.
Open source
the merged pull requests →Projects
browse all 33 →Selected publications
all 8 →GlucoKinaseDB: A comprehensive, curated resource of glucokinase modulators for clinical and molecular research Computational Biology and Chemistry, 2023
PepEngine: A Manually Curated Structural Database of Peptides Containing α, β- Dehydrophenylalanine (ΔPhe) and α-Amino Isobutyric Acid (Aib) International Journal of Peptide Research and Therapeutics, 2022
Statistical Enrichment Analysis of Samples: A General-Purpose Tool to Annotate Metadata Neighborhoods of Biological Samples Frontiers in Big Data, 2021
Education
Teaching and leadership
- President, Informatics Club, UAB (2023 - 2025). Grew computational training across departments through workshops, peer-learning sessions, and professional-development seminars.
- Certified Instructor, The Carpentries (2024 - Present). Taught workshops on R, Git, Bash, and Python at UAB's Biological Data Science Core.
Honors and certifications
- Claude Science Hackathon, one of 500 participants selected globally (2026)
- Google Cloud Research Credit Award, Google (2026)
- Elected Member, Tau Beta Pi Engineering Honor Society, UAB (2025)
- Blazer Graduate Research Fellowship, UAB (2022 - 2023)
- EMBL-EBI: Single-cell RNA-seq Analysis with Python (35 hours, Feb 2025)
- EMBL-EBI: Cancer Genomics and Transcriptomics (32 hours, May 2025)
- NVIDIA: Fundamentals of Deep Learning
The remaining 5 publications, 5 conference presentations and all 33 projects are on the full CV.
Last updated 2026-10-02