I’ve worked on the fundamental AI/ML for Self-driving Labs (SDLs) for over a decade. My first documented foray into the subject was in 2014, where I presented this novel idea in MRS of combining Bayesian statistics and methods decision-making under uncertainty to drive experimental decisions in order to optimize material properties in an efficient way. This type of work has since made its way into the mainstream SDL/Autonomous Experiments community.