Connor J. Taylor

University of Nottingham, University of Cambridge

Papers

Total Citations

H-Index

About

Connor J. Taylor is a pioneering researcher at the intersection of artificial intelligence, knowledge engineering, and autonomous scientific discovery. His primary research focuses on developing distributed self-driving laboratories—intelligent systems that autonomously design, execute, and analyze experiments across geographically dispersed facilities. Taylor’s major contribution lies in creating dynamic knowledge graph architectures that enable these laboratories to seamlessly share resources, data, and insights, effectively breaking down organizational silos. His most-cited work, "A dynamic knowledge graph approach to distributed self-driving laboratories" (2024, 73 citations), proposes a framework that transforms isolated experimental platforms into a collaborative, globally connected network. This innovation is particularly vital for tackling complex global challenges, such as climate change and pandemic response, which demand coordinated, large-scale scientific efforts. Taylor’s earlier foundational paper, "From Platform to Knowledge Graph: Distributed Self-Driving Laboratories" (2023, 12 citations), laid the groundwork for this vision. By integrating knowledge representation with automated experimentation, Taylor is shaping the future of accelerated, collaborative science, making him a key figure in the emerging field of AI-driven research infrastructure.