Evangelos is a Molecular Biologist interested in AI-enabled Synthetic Biology. He has worked extensively on mechanistic whole-cell models and, currently, he is focusing on Machine & Deep Learning approaches for genotype-to-phenotype tasks using high-throughput strain characterization data.
His research interests include generative neural networks for forward engineering of DNA and protein sequences, strategies for reducing data requirements in deep learning models for low-cost design of experiments pipelines, and the use of machine learning in rare diseases and orphan drugs. In his spare time, he is organising GOGEC, a global competition for genetic engineering.