Akshay Iyer

Computational biologist and immunologist, finishing my Ph.D. at the University of Miami (defending June 2026) alongside an M.Sc. in Data Science. My work lives at the intersection of single-cell multi-omics, machine learning, and human immunology, turning high-dimensional sequencing data into peer-reviewed biology.

At the Pahwa Lab and Miami CFAR, I built and maintain our end-to-end ECCITE-seq / CITE-seq analysis pipeline (Cell Ranger → Seurat / Scanpy → DSB normalization → WNN integration → scRepertoire / Trex), which has powered two iScience papers and underpins the longitudinal TARA pediatric HIV cohort. My doctoral thesis combines paired transcriptome + TCR + antigen-specificity analysis to track HIV-specific CD8⁺ T-cell clonotypes across the first eight years of childhood under early ART, resolving ten transcriptionally distinct CD8⁺ populations in the process.

Alongside the thesis, I've co-led mass cytometry (CyTOF) and scRNA-seq analyses for influenza-vaccine response studies in older adults living with HIV, and built supervised ML frameworks (scikit-learn / PyTorch) for HIV reservoir prediction and NK-cell cytotoxicity.

Day to day, I work in R (Seurat, Bioconductor, tidyverse), Python (Scanpy, pandas, scikit-learn, PyTorch), and on HPC/SLURM, with a strong bias toward reproducible, well-documented pipelines. I've also written a practitioner's guide to CyTOF in Frontiers in Immunology and mentor junior trainees on single-cell workflows.

Built and maintained the lab's end-to-end ECCITE-seq / CITE-seq pipeline (Cell Ranger v9 → Seurat / Scanpy → DSB normalisation → WNN integration → scRepertoire / Trex) used across the TARA cohort studies, including the iScience 2024 paper on accelerated CD8⁺ T-cell maturation in HIV-exposed infected infants.

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Developed HIV proviral integration-site mapping in host DNA via junction-read identification, surfacing host-genome integration loci in single-cell datasets.

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Owned the full computational data lifecycle for the TARA pediatric HIV clinical cohort — clinical-lab sample-metadata management, raw-data QC and storage, de-identification under IRB protocols, and public GEO submission, coordinating data delivery across the lab's clinical study workflow.

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Designed and led the single-cell multi-omic profiling study of ART-mediated remodelling of CD8⁺ T-cell stemness, exhaustion, and interferon memory in perinatally HIV-infected infants, defining ten transcriptionally distinct αβ CD8⁺ T-cell populations and HIV-specific clonotypes that persist across the first eight years of life (manuscript in preparation).

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Led the NK-cell study in the same TARA cohort, combining flow-based functional cytotoxicity assays with single-cell transcriptomics to demonstrate Fas/FasL-dependent NK-mediated killing of HIV-infected cells in infants with perinatal HIV (iScience, 2025).

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Led mass-cytometry (CyTOF) and scRNA-seq analyses for studies of standard- vs. high-dose influenza vaccination in older adults living with HIV, characterising how immune ageing shapes vaccine response.

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Built supervised ML and differential-abundance frameworks (scikit-learn / PyTorch; non-parametric tests with multiple-testing correction) for NK-cell killing assays in HIV cohorts, and predictive models of HIV reservoir size in pediatric populations.

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Co-led analysis on the impact of opioid-use disorder on influenza-vaccine antibody responses in people with HIV (OPIS cohort, Frontiers in Immunology, 2025).

PhD Immunology | MS Data Science| BS Biotechnology