I got my PhD from MIT in 2019 using deep learning to build the best model of the auditory brain. I was a Computational Science Graduate Fellow through the DOE and affiliated with the Center for Brains, Minds, and Machines. After that, I did a postdoc at Columbia and worked at an early-stage deep tech startup.
The papers I'm most proud of:
- Building better models of auditory cortical computation, using advances in deep learning.
See: 2018 Neuron paper and 2019 COiNb review.
(An overview of this and related work from Wired/Quanta.)
- Understanding how we robustly encode sound sources of interest in the presence of real-world background noise.