Eva Dyer

Eva Dyer is an Associate Professor at the Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania. She leads the Neural Data Science (NerDS) Lab, focusing on developing machine learning tools to decode brain activity and uncover computational principles of intelligence and behavior. Her research emphasizes cross-individual, cross-task, and cross-species generalization of neural models while promoting open-source software development for large-scale data analysis.

• NSF CAREER Award (2022) for interpretable neural modeling

Research Areas

Dr. Dyer's work sits at the intersection of neuroscience and machine learning, advancing:

• Scalable, interpretable deep learning architectures
• Self-supervised methods for neural time series
• Representation alignment across datasets and individuals
• Open-source tools for neuroimaging analysis

Her lab specifically investigates neural encoding/decoding mechanisms, brain-machine interfaces, and computational frameworks for understanding neural dynamics across multiple temporal and spatial scales.