Adrian Tan

Adrian Tan is a Senior Research Scientist at Q-CTRL, specializing in software design for optimal quantum performance through the characterization of tunable couplers. Previously held roles include Quantum Control Research Scientist, where Adrian focused on machine learning algorithms for quantum control, and an AI Resident at Normal Computing, exploring ML applications on thermodynamic hardware. Notable academic experience includes serving as a Graduate Research Assistant at Caltech, utilizing quantum computers for probing nature, and as a Graduate Teaching Assistant for a pioneering course on quantum algorithms. Additional internships at Amazon Web Services involved building cloud-based quantum simulation infrastructure, while earlier positions at DSO National Laboratories, Jublia, and research organizations in Singapore provided foundational experience in technical roles. Adrian holds a PhD in Applied Physics from Caltech and a Bachelor of Engineering with First Class Honours from the National University of Singapore.