Looking for interns!!!

Possible topics:

Quantization strategies for deep learning

Image and video compression

Deep neural networks pruning and compression

Efficiencing of Transformers for Computer Vision

Green AI

Fingerprinting in Deep Neural Networks

Knowledge distillation

Privacy preservation in imaging: towards the new GDPR

Neural Architecture Search towards efficient deep models

If interested, send CV, motivation letter and exams transcript here.


In a world where deep learning is becoming more and more the state-of-the-art, where the race to the computational capabilities determines the new technologies, it is crucial to open the black box deep learning is. Many good-willing researchers are already moving important steps in such direction, despite a wide multitiude and hetereogeneity of scientific backgrounds. This is good, this is progress!
We target it in the long term developing techniques which simplify these models. Some are easier to prune than others: why? How is the information being processed inside a deep model, from a macroscopic perspective? These are few of the questions to be answered to move in the right direction!

Green AI

Remotion of un-necessary neurons and/or synapses towards reduction of power consumption.

Model debiasing

Understand biases in data and cure the trained model.

Privacy in AI

Guaranteeing privacy in AI will be an important theme in the next years.

Understand the information flow

Modeling how the indormation is processed in deep models is our final goal.

Currently followed students