Eva Dyer




Assistant Professor
Primary School/Department: 
Wallace H. Coulter Department of Biomedical Engineering

Office Location: 
UAW 3108
Georgia Institute of Technology

Research Areas:

Research Areas: 

Research Interests:

Methods for quantifying neuroanatomy

The lab is actively developing data analysis methods for learning cytoarchitectonics (layers), mapping brain areas, and distributed segmentation and analysis of large-scale neuroimaging data.

Low-dimensional signal models

Unions of subspaces (UoS) are a generalization of single subspace models that approximate data points as living on multiple subspaces, rather than assuming a global low-dimensional model (as in PCA). Modeling data with mixtures of subspaces provides a more compact and simple representation of the data, and thus can lead to better partitioning (clustering) of the data and help in compression and denoising.

Analyzing the activity of neuronal populations

Advances in monitoring the activity of large populations of neurons has provided new insights into the collective dynamics of neurons. The lab is working on methods that learn and exploit low-dimensional structure in neural activity for decoding, classification, denoising, and deconvolution.

Large-scale optimization

Optimization problems are ubiquitous in machine learning and neuroscience. The lab works on a few different topics in the areas of non-convex optimization and distributed machine learning.