Aria Wang • 王 元

I am a joint PhD student in Neural Computation and Machine Learning at Carnegie Mellon University. I am advised by Mike Tarr and Leila Wehbe.

I study visual and semantic processing in the human brain. In my work, I collect data using functional Magnetic Resonance Imaging (fMRI) and use models from computer vision and natural language processing to model brain responses of viewing natural images and movies.

Before joining CMU, I received a B.A. in Cognitive Science and Statistics from UC Berkeley.

Other than research, I enjoy rock climbing, mountaineering, cooking, and reading.

Publications and Preprints

Incorporating Natural Language into Vision Models Improves Prediction and Understanding of Higher Visual Cortex [paper] [poster] [talk]
Aria Y. Wang, Kendrick Kay, Thomas Naselaris, Michael J. Tarr, Leila Wehbe
In Review.

Food for Thought: Selectivity for Food in Human Ventral Visual Cortex [paper]
Nidhi Jain, Aria Y. Wang, Margaret M Henderson, Ruogu Lin, Jacob S Prince, Michael J. Tarr, Leila Wehbe
In Review.

Joint Interpretation of Representations in Neural Network and the Brain [paper]
Aria Y. Wang*, Ruogu Lin*, Michael J. Tarr, Leila Wehbe
ICLR Workshop 2021

Neural Taskonomy: Inferring the Similarity of Task-Derived Representations from Brain Activity [paper] [poster] [website]
Aria Y. Wang, Michael J. Tarr, Leila Wehbe
Neural Information Processing Systems (NeurIPS) 2019

Learning Intermediate Features of Object Affordances with a Convolutional Neural Network [paper]
Aria Y. Wang, Michael J. Tarr
Conference on Cognitive Computational Neuroscience (CCN) 2018

*Equal contribution

Conference and Workshop Presentations

Expanding Visual Feature Spaces towards a General Encoding Model of Scene Perception
Aria Y. Wang, Michael J. Tarr, Leila Wehbe
Poster presented at Society for Neuroscience (SfN) 2019

Neural Taskonomy: Inferring the Similarity of Task-Derived Representations from Brain Activity
Aria Y. Wang, Leila Wehbe, Michael J. Tarr
Poster presented at Algonauts Workshop at MIT

Learning Intermediate Features of Affordances with a Convolutional Neural Network
Aria Y. Wang, Michael J. Tarr
Poster presented at Conference on Cognitive Computational Neuroscience (CCN) 2018

Learning Intermediate Features of Affordances with a Convolutional Neural Network
Aria Y. Wang, Michael J. Tarr
Poster Presented at Annual Meeting of the Vision Science Society (VSS) 2018

*Equal contribution