Applications:
Computer Science, Engineering, Healthcare Research
Methodologies:
Artificial Intelligence, Computing, Data Mining, Image Data, Information Theory, Machine Learning, Optimization

Qing Qu

Assistant Professor

EECS, College of Engineering

Assistant Professor of Electrical Engineering and Computer Science, College of Engineering

His research interest lies in the intersection of signal processing, data science, machine learning, and numerical optimization. He is particularly interested in computational methods for learning low-complexity models from high-dimensional data, leveraging tools from machine learning, numerical optimization, and high dimensional geometry, with applications in imaging sciences, scientific discovery, and healthcare. Recently, he is also interested in understanding deep networks through the lens of low-dimensional modeling.


Accomplishments and Awards