Manuel has a solid ten-year track record in bioinformatics, statistical analysis, and data science applied to complex biological problems. He drives the development of advanced computational solutions at Microomics, where he integrates omics analysis and NGS pipelines to transform biological data into useful knowledge.
He has a PhD in Biomedical Sciences, skillful in metagenomics, genomic surveillance, and the development of reproducible analysis workflows. He has led projects ranging from the detection of emerging viruses and microbiome studies to the development of molecular surveillance systems for diseases such as malaria, using machine learning and artificial intelligence. Manuel is an expert in programming in Python and R, statistical modelling, data mining, and workflow automation using tools such as Nextflow, Singularity, Conda, and Docker.
Manuel has published ten scientific papers and has a proven track record of international collaboration. He is renowned for his ability to design robust solutions, communicate complex results clearly and foster work environments where science and technology converge to solve real-world challenges. His approach combines accuracy and creativity with a deep conviction that bioinformatics is at its most powerful when accessible and reproducible.