Compressed Sensing

For compressed sensing, I am had research experience on Applactions of compressed sensing, Perturbed compressed sensing, Deep compressed sensing.

Applications of compressed sensing

Thesis

Perturbed compressed sensing

my recent interest is to develop perturbed compressed sensing theory, which not only consider the measurement noise but also take the noise of the sensing matrix into account.

Deep compressed sensing

For deep learning, I am deeply passionate about advancing the capabilities of neural networks through innovative models for vision tasks.

I am currently focused on exploring new models, such as Mamba, to replace traditional Transformer-based architectures. My goal is to achieve more efficient representation and reduced complexity in neural networks. My research particularly targets vision tasks like image compressed sensing, where the objective is to recover higher quality images using fewer samples, requiring enhanced expressive power in neural networks.