Anestis Gkanogiannis

Anestis Gkanogiannis is an independent AI, machine learning, and genomics practitioner whose work combines computational biology with practical software development. With around 15 years of experience, he builds open-source, production-grade tools and reproducible workflows for large-scale biological data. He maintains the Bioconductor packages fastreeR, metabinR, and jvecfor, and develops agentic tools that use large language models to run bioinformatics workflows from natural-language requests.

His expertise spans genome assembly and annotation, population and comparative genomics, genome-wide association studies, genomic selection, metagenomics, and the analysis of next-generation sequencing and functional-genomics data. His services and technical work include algorithm design, pipeline development, multi-omics data analysis, and software development for research applications, supported by experience with high-performance computing. He works with technologies including C++, Java, R, Nextflow, and Docker or Singularity. His current focus is applying embeddings, deep learning, and AI agents to make complex omics datasets easier and faster to investigate. Gkanogiannis also shares publications and project information and welcomes research collaborations.