2015-2018 WRF and Moore/Sloan Postdoctoral Fellow, Statistics
Specializations
Health Sciences, Statistics
Nick Foti was a Moore/Sloan Data Science and WRF Innovation in Data Science Postdoctoral Fellow from 2015-2018. He is currently a research scientist at the Computer Science and Engineering (CSE) department at University of Washington.
Biography
Institute for Neuroengineering
UW mentors
Emily Fox, Statistics
Adrian K.C. Lee, Speech & Hearing Sciences
Education history
Ph.D., Computer Science, Dartmouth College, 2013
B.S., Computer Science and Mathematics, Tufts University, 2007
Research goals
Nick Foti’s research focused on the development of Bayesian nonparametric statistical methods applied to machine learning. In particular, he develops models and scalable inference algorithms applicable to data arising from various dynamic complex phenomena including finance, genomics, and neuroscience, among others.
As a joint UWIN and eScience WRF Postdoctoral Fellow, he developed statistical models to learn the effective connections between the auditory sensory areas of the brain and the attentional network from high-dimensional time series of magnetoencepholography (MEG) recordings.