Aria Wang

Background

About Aria Wang

I'm a Research Scientist in the Machine Learning Core at the NIH/NIMH, where I work closely with experimentalists across disciplines to understand the computations carried out by the brain. My primary focus is on integrating end-to-end, task-driven learning framework into closed-loop experiments involving behavioral and neuronal interventions—aiming to reveal the mechanisms and objectives underlying neural processing. I earned a joint PhD in Neural Computation and Machine Learning from Carnegie Mellon University, where I was advised by Mike Tarr and Leila Wehbe. My doctoral research focused on modeling visual and semantic processing in the human brain, leveraging fMRI data and models from computer vision and natural language processing to predict brain responses to naturalistic stimuli such as images and movies. I hold a B.A. in Statistics and Cognitive Science from UC Berkeley.