Latest news

[Mar 26] Article accepted for publicatin at IEEE Transactions on Circuits and Systems for Video Technology: Compression in 3D Gaussian Splatting: A Survey of Methods, Trends, and Future Directions. Muhammad Salman Ali, Chaoning Zhang, Marco Cagnazzo, Giuseppe Valenzise, Enzo Tartaglione, Sung-Ho Bae.

[Feb 26] Paper accepted at CVPR 2026: Bias In, Bias Out? Finding Unbiased Subnetworks in Vanilla Models.

[Dec 25] I have been promoted to the rank of Full Professor

[Nov 25] Article accepted for publication at Neurocomputing: TEP-ones: A Simple yet Effective Approach for Transferability Estimation of Pruned Backbones

[Nov 25] Article accepted for publication at IEEE Transactions on Multimedia: Security and Real-time FPGA integration for Learned Image Compression

Professorships, PhDs and stages applications are now open!

One tenure track position on animation with AI will open soon (with funding to recruit a PhD/postdoc)!


PhD positions are now available spanning multimodality and efficiency! Reach out for more info


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Mission

In a world where deep learning is becoming more and more state-of-the-art, where the race to computational capabilities determines new technologies, it is crucial to open the black box that deep learning is. Many researchers are already moving important steps in such direction, despite a wide multitude and heterogeneity 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 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.

Explore an interactive map of every paper, grouped by research theme.

Open the research graph
Imad Eddine Marouf

Imad Eddine Marouf

PhD student
Efficient transformers for computer vision
Co-supervised with Stéphane Lathuilière
Yinghao Wang

Yinghao Wang

PhD student
Foundation models for EEG treatment
Co-supervised with Van-Tam Nguyen

Zhu Liao

Zhu Liao

PhD student
Deep Neural Network pruning
Co-supervised with Van-Tam Nguyen


Dorian Gailhard

Dorian Gailhard

PhD student
Generative models and Graph Neural Networks for SoCs
Co-supervised with Jhony H. Giraldo
Lê Trung Nguyen

Lê Trung Nguyen

PhD student
Methods for on-device training

Co-supervised with Van-Tam Nguyen
Ivan Luiz De Moura Matos

Ivan Luiz De Moura Matos

PhD student
Debiasing through NAS
Previously: Stage M2 Oct 23-Feb 24
Leonardo Magliolo

Leonardo Magliolo

PhD student
Information flow in Deep Neural Networks

Rayyan Ahmed

Rayyan Ahmed

PhD student
Explaining and Removing Social Biases in Text-to-Image Generative AI
Co-supervised with Stephan Alaniz
Kian Bakhtari

Kian Bakhtari

PhD student
Efficient foundation models exploitation for autonomous driving
Co-supervised with Stephan Alaniz
Mohamed Salaheldin

Mohamed Salaheldin

PhD student

Co-supervised with Kaouther Messaoud
Charles Herr

Charles Herr

Research path student
Learning alternatives to backpropagation
Yiming Yang

Yiming Yang

Stage M1
3D Gaussian Splatting generation
Huanshan Huang

Huanshan Huang

Stage M2
Input frame compression for deep video processing
Previously: Stage M1 Apr-Aug 2025

Formerly advising