Yuanning Li, Ph.D. [CV]
I am currently a postdoctoral scholar in the Department of Neurological Surgery at the University of California, San Francisco, where I work with Edward Chang. In the Chang Lab, I use human electrophysiology and computational methods to study the neural basis of speech perception.
Prior to UCSF, I completed my PhD in the joint Program in Neural Computation & Machine Learning at Carnegie Mellon University and the University of Pittsburgh, where I was co-advised by Avniel Ghuman (with Pitt Neurological Surgery) and Max G’Sell (with CMU Statistics). I also collaborated with Mark Richardson and Julie Fiez on various research projects over the course of my PhD.
Before my PhD, I received Master’s degree in Electrical & Computer Engineering from Carnegie Mellon and Bachelor’s degree in Electrical Engineering from the School of Advanced Engineering at Beihang University.
My research interests primarily lie in the intersection between computational and cognitive neuroscience. The two main goals of my research are:
- to understand how different aspects of high-level sensory information are represented and processed in neural populations, underlying cognitive processes such as speech perception and reading;
- to build computational models of these perceptual processes in the brain.
To achieve these goals, I develop and apply statistical machine learning methods to analyze large-scale neural data recorded using ECoG, MEG and fMRI.