Quantum metrology has become increasingly precise in probing fundamental laws of physics, especially with the recent experimental breakthroughs that transform atoms and molecules into quantum sensors. However, for decades it has remained a formidable challenge to protect such quantum sensors against environmental noise, system drift, and imperfections in the experimental control. In this project, we aim to integrate physics-informed learning and reinforcement learning into a closed-loop and autonomous control of a laser platform, which will be used in our quantum metrology experiment. Registration is mandatory on the following website: https://indico.frib.msu.edu/event/87/