Creative and self-motivated Deep Learning enthusiast with a special curiosity to learn new things. My current Ph.D. research activity is focused on the development of a deep learning-based platform entitled DeepRetro: a computational framework for retrosynthesis and pathway design towards optimizing compound bioproduction. In this work, a computational framework for retrosynthesis and pathway design, based on reinforcement learning algorithms, using deep neural networks and state-of-the-art optimization algorithms, to search for biological pathways, from available precursors to target molecules, through the use of known and newly generated putative reactions and metabolites will be developed.I was also involved in the development of machine learning-based tools for the selection and design of chemical compounds. This working program was inserted in a new H2020 EU funded “ShikiFactory 100: Modular cell factories for the shikimate pathway”