I work in the Google Brain Team at Google Research, where I focus on biologically inspired computing. In particular, I am interested in automatic machine learning (AutoML), evolutionary computation, and the relationship between biological and artificial neural networks. My current work aims to study the emergence of ML strategies in an in-silico evolutionary process with minimal human bias (Google Research blog post). You can find a selection of my publications in my resume and a complete list in my Google Scholar page.
Before Google, I did a physics Ph.D. under the supervision of Markus Meister (biology department) at Harvard University. My dissertation studied the neurophysiology of the retina from a machine learning standpoint. I built neural network models with correct anatomical structure to learn from their living biological counterparts. By learning to predict what the eye would tell the brain, these machine learning models also discover internal retinal physiology.
You can find my contact information here.