The team is recognized for pioneering the field of machine learning for quantum control. They designed and led the first ever in-situ experimental validation of fully automated calibration of semiconductor quantum dot devices, a leading candidate platform for quantum computing. Their groundbreaking work combining machine learning, computer vision, and physics-based models to enable intelligent automation of quantum experiments initiated a whole new field within the semiconductor community that now involves multiple research groups around the world.