Samuel Failor

Samuel Failor is a postdoctoral researcher currently studying the neural correlates of learning and behavior in the visual cortex at University College London. Having served as a Research Fellow in the Cortex Lab from 2015 to 2024, they focused on how learning and experience influence stimulus representations. Samuel participated in several prestigious fellowships, including the Faculty AI Data Science Fellowship and the S2DS Fellowship, where they gained significant experience in data science and machine learning. They currently hold the position of Senior Machine Learning Engineer at Clavata. Samuel is pursuing a PhD in Neuroscience from the University of California, Davis, and holds a Bachelor of Science in Cognitive Science from the University of California, San Diego.