Bio

I am a post-doctoral research associate with the Department of Electrical & Computer Engineering at Carnegie Mellon University. In May, I defended my dissertation, titled "Interpreting neural population activity during sensorimotor control," which was awarded the A.G. Milnes Best Thesis Award. I am advised by Professors Byron Yu and Steve Chase.

Contact information:

CV available upon request.

Research interests

Machine Learning

Probabilistic latent variable models, including linear-Gaussian models, Gaussian processes, and deep networks.

Neural Data Analysis

How can we use machine learning to extract meaning from neural recordings? What new statistical techniques are needed to test hypotheses about brain function and circuitry?

Brain-machine Interfaces (BMIs)

By translating intracortical recordings into signals for driving prosthetic devices, BMIs offer restored movement and communication for those with spinal cord injuries, neurodegenerative diseases or limb amputations.