Donovan Buterakos is a postdoc at the University of Maryland Joint Center for Quantum Information and Computer Science (QuICS) and a guest researcher at the National Institute of Standards and Technology (NIST). His research entails using machine learning techniques to automate the tuning of quantum dot devices. This involves using deep learning, neural networks, and computer vision techniques to process and annotate measurement data. He also works with device simulations in order to generate large amounts of labeled data which can be used to train machine-learning models. Donovan has received a Ph.D. from the Condensed Matter Theory Center at University of Maryland, and has obtained a B.S. and M.S. in physics from Virginia Tech.