Dyer’s research interests lie at the intersection of machine learning, optimization, and neuroscience. Her lab develops computational methods for discovering principles that govern the organization and structure of the brain, as well as methods for integrating multi-modal datasets to reveal the link between neural structure and function.
Georgia Institute of Technology
Eva Dyer’s research combines machine learning and neuroscience to understand the brain, its function, and how neural circuits are shaped by disease. Her lab, the Neural Data Science (NerDS) Lab, develops new tools and frameworks for interpreting complex neuroscience datasets and building machine intelligence architectures inspired by the brain. Through a synergistic combination of methods and insights from both fields, Dr. Dyer aims to advance the understanding of neural computation and develop new abstractions of biological organization and function that can be used to create more flexible AI systems.