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About

Vincenza Dragone is a leading researcher at the intersection of organic chemistry and artificial intelligence, pioneering the development of autonomous systems for chemical discovery. Her most impactful work centers on integrating machine learning with robotic platforms to automate and accelerate the search for new chemical reactivity. In her landmark 2018 study, “Controlling an organic synthesis robot with machine learning to search for new reactivity,” which has garnered over 770 citations, Dragone demonstrated a closed-loop system where a robotic platform, guided by a machine-learning algorithm, autonomously explores reaction space, identifies promising reactivity, and iteratively optimizes conditions without human intervention. This breakthrough dramatically reduces the time and labor traditionally required for reaction discovery. Her earlier 2017 paper, “An autonomous organic reaction search engine for chemical reactivity,” introduced a system capable of evaluating reactivity across a network of 64 possible reactions, bypassing the need for separate work-up and separation steps. Dragone’s work has fundamentally shifted how chemists approach reaction discovery, enabling high-throughput, unbiased exploration of chemical space. Her contributions are widely recognized as foundational to the emerging field of self-driving laboratories, making her a key figure in the future of automated chemical synthesis.