Emily Rounds, Phd

Investigator

Emily’s work integrates computational modeling and cognitive neuroscience to explore the principles of learning in the biological brain. At Deep Valley labs, she brings knowledge of bio-inspired and brain-based computation to bear on achieving generalized learning capabilities in artificial intelligences. Her previous work focused on the development of a generalizable evolutionary framework that could train generic spiking neural networks to replicate the functional behavior observed at the level of individual neurons as well as the population. She has a Ph.D. and M.S. from the University of California, Irvine in Cognitive Neuroscience and a B.S. from Pacific University in Psychology.