My research interests are in the fields of signal and image processing, machine learning, optimization, and their interconnections.

My lines of research include (but not limited to):

• Solving inverse problems (e.g., super-resolution, inpainting, etc.) using deep data-driven priors (e.g., denoisers, GANs, and diffusion models)

• Exploring the evolution of features in deep neural networks (e.g., various strategies for analyzing and experimenting neural collapse of overtrained classifiers)

• Developing efficient optimization frameworks for signal recovery and parameter estimation, and analyzing their convergence / performance

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I'm looking for self-motivated graduate students with strong academic record that are interested in doing research on theory and applications in these fields. If you are interested, you are more than welcome to send me an email with your CV and academic record so I can understand your background.

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