Stavros Bouras

CoEvolution: A Comprehensive Trustworthy Framework For Connected Machine Learning And Secure Interconnected AI Solutions

Enabling Adversarial Robustness in AI Models Through Kubeflow MLOps

Privacy Evaluation of Generative Models for Trajectory Generation

Adversarially Guided Diffusion for LiDAR Range Image Synthesis

LiDAR semantic segmentation is a key perception task in autonomous driving, where false predictions can affect downstream planning and safety-critical decision-making. Although adversarial...

Enabling Adversarial Robustness in AI Models through Kubeflow MLOps

AI models are increasingly deployed in cloud-native environments to support scalable and automated services. However, while platforms such as Kubernetes provide strong infrastructure...

Privacy Evaluation of Generative Models for Trajectory Generation

Trajectory data is fundamental to modern urban intelligence, yet its sensitivity raises significant privacy concerns. Generative models such as Generative Adversarial Networks, Variational...

A Comparative Study of Federated Learning Aggregation Strategies under Homogeneous and Heterogeneous Data Distributions

Federated Learning has emerged as a transformative paradigm for collaborative machine learning across distributed environments. However, its performance is strongly influenced by the aggregation...