AI-driven virology insights

Designing intelligent systems for viral discovery

I'm Alan Carbajo, a researcher at Wayne State University School of Medicine working with Dr. Phil Pellett to explore how machine learning can accelerate breakthroughs in virology and genomic design.

Currently exploring
  • Generative DNA design workflows guided by deep learning
  • Predictive models that capture viral behavior and tropism
  • Interactive data visualizations that tell scientific stories
Latest focus

Mapping latent genomic representations for antiviral discovery.

About the journal

Exploring the intersection of artificial intelligence and virology

This journal documents experiments, prototypes, and reflections from my work designing computational tools for virology. I share lessons from the lab, notes from current projects, and ideas that push the boundaries of how we model and design biological systems.

Scientific storytelling

I translate complex datasets into intuitive visual narratives—bridging researchers, clinicians, and broader audiences with interactive dashboards and exploratory tools.

Systems thinking

By combining genomics, epidemiology, and machine learning, I develop end-to-end workflows that move from raw sequencing data to actionable hypotheses and design insights.

Machine learning

Designing advanced models that learn latent viral patterns and predict phenotypic behavior.

Viral genomics

Generating and analyzing viral genomes with neural networks for design and discovery.

Epidemiology

Modeling population-level spread to inform responses during outbreaks and emerging threats.

Recent projects

Putting intelligent pipelines into practice

Selected work that blends computational research, design, and scientific communication.

Latest writing

Notes, experiments, and observations from the lab

Insights on AI-driven biology, research tooling, and the craft of storytelling.

Contact

Get in touch

Have a question or want to say hello? I’d love to hear from you.