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Nesryne Mejri serves as a Postdoctoral Researcher at the Interdisciplinary Centre for Security, Reliability and Trust (SnT), University of Luxembourg, within the Computer Vision, Imaging & Machine Intelligence (CVI2) research group led by Prof. Djamila Aouada. Her office is located at BLE, E02 011. She earned her Master's degree in Information and Computer Science from the University of Luxembourg in 2021. Her academic trajectory demonstrates a focused progression into advanced visual intelligence research. Dr. Mejri's primary research centers on Computer Vision and Deep Learning , with specialized expertise in media forensics and detection of forged visual content . Her work directly addresses critical security challenges in the digital age, particularly the proliferation of deepfakes and synthetic media manipulation. This research combines theoretical machine learning advances with practical applications for media authentication. As part of the CVI2 group, she contributes to cutting-edge projects developing robust forensic methodologies under Prof. Aouada's supervision. No information is available regarding students she has advised or specific research grants secured. Her current efforts focus on enhancing detection capabilities for increasingly sophisticated visual forgeries.

• Computer Vision
• Deep Learning
• Media Forensics
• +1 more

Marcella ASTRID is a Researcher at the University of Luxembourg's Interdisciplinary Centre for Security, Reliability and Trust (SnT), specifically within the CVI2 department. Her research focuses on advanced machine learning techniques applied to cybersecurity and computer vision challenges, particularly in the detection of synthetic media (deepfakes) and anomaly detection systems. She specializes in developing robust models that address vulnerabilities in adversarial scenarios and improve generalizability across diverse datasets. Key research areas include deepfake detection through spatio-temporal analysis, anomaly detection via novel training paradigms, and efficient neural network compression for resource-constrained environments. Her work bridges theoretical advancements in machine learning with practical applications in surveillance systems, autonomous robotics, and cybersecurity infrastructure. Recent contributions emphasize leveraging autoencoder weaknesses, pseudo anomaly generation, and localized attention mechanisms to enhance detection accuracy and model robustness. Marcella’s research also explores cross-modal learning (audio-visual synchronization) and semi-supervised methodologies to tackle data scarcity issues in critical domains like battery thermal imaging and multi-camera traffic classification. She actively publishes in top-tier venues and collaborates on interdisciplinary projects addressing real-world security and reliability challenges.

• Computer Vision
• Deep Learning
• Cybersecurity
• +3 more

Djamila Aouada is an Assistant Professor and Senior Research Scientist at the University of Luxembourg's Interdisciplinary Centre for Security, Reliability and Trust (SnT), where she heads the Computer Vision, Imaging, and Machine Intelligence (CVI2) research group. She earned her State Engineering degree from École Nationale Polytechnique, Algeria, and PhD from North Carolina State University. Her research spans computer vision, signal processing, pattern recognition, and data modeling. Dr. Aouada leads several national and European projects including FNR FAVE, 3D-Act, and H2020 STARR, focusing on AI-driven solutions for industrial and security applications. She has received four IEEE Best Paper Awards for her contributions. Dr. Aouada has supervised 5 completed PhD theses and currently mentors 5 PhD candidates, while maintaining collaborations with Los Alamos National Laboratory and Mitsubishi Electric Research Labs. She serves as Senior IEEE Member and previously chaired IEEE Benelux Women in Engineering.

• Computer Vision
• Signal Processing
• Image Processing
• +3 more