Stella Yu

734-647-1761

Applications:
Computer Science, Earth Science and Ecology, Engineering, Environmental and Climate Research, Healthcare Research, Physical Science
Methodologies:
Artificial Intelligence, Computer Vision, Graph-Based Methods, Machine Learning

Stella Yu

Professor

CSE

Professor of Electrical Engineering and Computer Science, College of Engineering

My research lies at the intersection of computer vision, human vision, and machine learning. Visual perception presents not just a fascinating computational problem, but more importantly an intelligent solution for large-scale data mining and pattern recognition applications.
My research has thus three themes.
1. Actionable Representation Learning Driven by Natural Data. I attribute our fast effortless vision to actionable representation learning driven by natural data, where mid-level visual pieces can be reassembled and adapted for seeing the new.
2. Efficient Structure-Aware Machine Learning Models. I view a computational model as dual to the data it takes in; since visual data are full of structures, models reflective of such structures can achieve maximum efficiency.
3. Application to Science, Medicine, and Engineering. I am interested in applying computer vision and machine learning to capture and exceed human expertise, enabling automatic data-driven discoveries in science, medicine, and engineering.


Accomplishments and Awards