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About

Paloma L. Prieto is a pioneering researcher at the intersection of chemical automation, data science, and artificial intelligence, whose work is reshaping how modern scientific discovery is conducted. Her research focuses on the development of automated and self-driving laboratory systems that integrate robotics, machine learning, and computer vision to accelerate experimental workflows in chemistry. Prieto's most influential contributions include critically examining the promises and pitfalls of laboratory automation in her widely cited "Automation isn't automatic" (2021, 128 citations), and exploring how data science and machine learning can be synergistically combined with experimental chemistry in "Automated Experimentation Powers Data Science in Chemistry" (2021, 110 citations). Her innovative automated solubility screening platform, which leverages computer vision rather than traditional analytical techniques, demonstrates her commitment to practical, accessible solutions for routine but labor-intensive chemical processes (74 citations). More recently, her development of IvoryOS — an interoperable web interface for orchestrating self-driving laboratories — highlights her forward-thinking approach to standardizing and democratizing autonomous experimentation. Collectively, Prieto's work has garnered over 300 citations, establishing her as a leading voice in the future of intelligent, automated chemical research.