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About

Riley J. Hickman is a pioneering researcher at the intersection of artificial intelligence, robotics, and materials science, with a focus on autonomous experimentation and accelerated scientific discovery. Hickman's most influential work centers on the development of self-driving laboratories (SDLs)—closed-loop, AI-driven platforms that integrate machine learning, robotics, and high-performance computing to autonomously design and execute experiments. His landmark paper on the delocalized, asynchronous discovery of organic laser emitters (2024, 130 citations) demonstrated that cloud-based strategies could coordinate multi-site research workflows, dramatically accelerating materials discovery across geographically distributed teams. A key architectural contribution is his development of Atlas, a decision-making framework serving as the "brain" for self-driving laboratories, which has garnered significant attention across two publications totaling nearly 50 citations. Hickman has also advanced optical monitoring techniques for polymerization reactions and explored the transformative potential of AI and robotics in pharmaceutical formulation. His work collectively addresses one of modern science's central challenges: compressing the time and cost of discovery pipelines. With over 230 citations across his most prominent works, Hickman is emerging as a leading voice in the autonomous science movement, reshaping how researchers approach experimental design and materials development.