Anis KACEM

Anis KACEM is a Researcher at the Interdisciplinary Centre for Security, Reliability and Trust (SnT) within the University of Luxembourg, part of the Signal Processing and Satellite Communications (SIGCOM) research group. His work focuses on Computer Vision and Pattern Recognition, particularly in Human Behavior Understanding from visual data. He received his PhD in Computer Science from the University of Lille (France) in 2018.

Research interests include advanced topics such as Earth Observation via multi-modal autoencoders, domain adaptation for image classification, vulnerability-aware deepfake detection, and CAD system reverse engineering. His contributions span neural network pruning, 3D shape analysis, and generative models for medical imaging.

Publications highlight innovations in spatio-temporal learning for deepfake detection, hybrid attention mechanisms for pedestrian detection, and tool-augmented CAD task solvers. His work bridges theoretical advances with practical applications in autonomous systems and space technology.

Notably, he has contributed to challenges like the SHARP 2023 Challenge on CAD history recovery and developed frameworks like Picasso for CAD sketch inference using self-supervised learning.