Yifan Qu

Hi, I'm Yifan

Google Scholar • LinkedIn •
GitHub •
quyf [at] cs [dot] toronto [dot] edu

About Me

I am Yifan Qu, a PhD student at University of Toronto, advised by Prof. Christina Christara. My research interests are graph neural networks, numerical methods, and scientific computing. My previous work focuses on developing efficient computational methods for PDE-based models, numerical algorithms, and image processing.

I received my undergraduate degree (BSc Honours) in Applied Mathematics and Computational Mathematics from the University of Waterloo, where I was advised by Prof. Hans De Sterck and Prof. Andrea Scott.

Outside of research, I enjoy photography, piano, ballet, and figure skating, and I am always eager to explore interdisciplinary collaborations.

Projects

River Ice Classification with GNNs

Developed a learnable edge-weight GNN for SAR image classification, achieving a 10% accuracy improvement over CNNs.

PDE-Based GNNs

Designed deep GNN architectures using first-order PDEs to mitigate over-smoothing and enhance learning in deep networks.

Underwater Image Dehazing

Improved the Dark Channel Prior (DCP) method, reducing mean squared error by 10%.

Contact

Let's connect!