Zack Tidwell is a machine learning and optimization specialist who enjoys distilling problems to their most basic forms in order to develop robust, generalizable solutions. His research experience spans a diverse array of domains, including healthcare, meteorology, and gaming, as well as a variety of solution spaces, including neural networks, reinforcement learning, and spatial-temporal data mining. Notably, he developed spatial-probability trees for expert move prediction in computer Go, as well as machine-learning methods for CAPTCHA recognition. His current projects focus on distributed systems for personal computing and automated techniques for de-siloing large legacy datasets. He holds an M.S. in Computer Science from the University of Oklahoma.