Daniel Olds

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About

Daniel Olds is a leading figure in the development of autonomous, high-throughput experimentation at scientific user facilities. His research focuses on integrating robotics, artificial intelligence, and real-time data analysis to revolutionize materials characterization. Olds’s major contribution is the conceptualization and implementation of "enterprise beamlines," which leverage low-cost automation and AI/ML to deliver multi-modal materials analysis at unprecedented speeds. His 2022 paper on this topic, with 6 citations, outlines a framework for dramatically reducing the barrier to entry for accelerated materials discovery. Building on this, his 2025 work on robotic integration for end-stations, cited 3 times, introduces a "robotic beamline scientist" system that uses ROS2 and Bluesky tooling for adaptive sample management. This work is pivotal for enabling fully autonomous, closed-loop experimentation at synchrotrons and neutron sources. Olds’s vision is transforming how researchers interact with large-scale facilities, moving from manual, serial experiments to intelligent, parallelized discovery pipelines. His achievements are central to the next generation of materials science infrastructure.