Alex Williams, Ph.D.Associate Research Scientist, Statistical Analysis of Neural Data, CCN, Flatiron Institute
Assistant Professor, Center for Neural Science, New York University
Alex is jointly appointed as an Assistant Professor in the Center for Neural Science at NYU and an Associate Research Scientist / Project Leader at the Flatiron Institute. Alex develops statistical models to characterize functional flexibility in large-scale neural circuits—e.g., how the dynamics of large neural ensembles change when learning a new skill, during periods of high attention or task engagement, or over the course of development and aging.
Alex performed his postdoctoral work in the Statistics Department at Stanford University working with Scott Linderman’s research group. Before that, he obtained a PhD in Neuroscience from Stanford with supervision from Surya Ganguli. He has also worked at Google Brain (with David Sussillo), Sandia National Labs (with Tamara Kolda), the Salk Institute (with Terry Sejnowski), and Brandeis University (with Eve Marder) as a visiting researcher / technician. He first began studying neuroscience as an undergraduate at Bowdoin College, where he was advised by Patsy Dickinson.
SURF Project: This project analyzes camera and microphone array recordings of Mongolian gerbil families in collaboration with labs run by Professors Dan Sanes and David Schneider at New York University (NYU). Gerbils are highly social rodents — more so than typical laboratory species — and they produce elaborate vocal call sequences in their social interactions. From these video and audio data, this project aims to extract all vocalizations and identify which gerbil produced them (a problem known as speaker diarization). To achieve this, the team plans to utilize deep convolutional networks accompanied by methods to quantify uncertainty in deep learning models. A SURF fellow will implement these deep network models in Python and help curate the video and audio datasets (e.g., flagging and removing mislabeled video frames). The fellow will also aid in the collection of behavioral data.
Fellow: Claire Zhang