Gamaleldin F. Elsayed is an AI resident at Google Brain interested in deep learning and computational neuroscience research. In particular, his research is focused on studying properties and problems of artificial neural networks and designing better machine learning models with inspiration from neuroscience. In 2017, he completed his PhD in Neuroscience from Columbia University at the Center for Theoretical Neuroscience with John P. Cunningham. During his PhD, he contributed to the field of computational neuroscience through designing machine learning methods for identifying and validating structures in complex neural data. Prior to that, he completed his B.S. from The American University in Cairo with a major in Electronics Engineering and a minor in Computer Science, and earned M.S. degrees in electrical engineering from KAUST and Washington University in St. Louis. Before his Graduate studies, he was also a professional athlete and Olympian Fencer. He competed at The 2008 Olympic Games in Beijing with the Egyptian Saber team.