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Biometry Research Group (BioRG) @ IPLAB

The Biometry Research Group (BioRG) - Center for Biometric Security, Artificial Intelligence & Forensics - is a research unit committed to advancing the state of the art in Computer Vision and Machine/Deep Learning for biometric recognition, multimedia security, and data integrity. BioRG is directed by Prof. Alessandro Ortis, Associate Professor in Computer Science at the Univerisity of Catania, teacher of Multimedia Security and Biometry, IEEE Senior Member and member of the IEEE Biometrics Council. The group’s mission is to design, develop, and evaluate AI-based methodologies capable of addressing key challenges in biometric authentication, surveillance, privacy protection, and multimedia forensics.

BioRG’s research is deeply rooted in the analysis and processing of visual, audio, and multimodal data, with a strong focus on both theoretical advancements and real-world applications. Core topics include fingerprint recognition (including latent reconstruction), face and gait analysis, presentation attack detection, and soft biometrics, as well as forensic analysis of manipulated images and videos.

The group also explores novel machine learning paradigms, with particular attention to explainability, adversarial robustness, and model generalization across domains. A significant part of the research investigates the integration of AI methods with edge computing frameworks, privacy-preserving learning approaches, and multimodal fusion techniques for robust identity verification.

Key research topics include, but are not limited to:

  1. Multimodal biometric authentication (face, voice, fingerprint, gait, etc.);
  2. Latent fingerprint enhancement and identity-preserving reconstruction;
  3. Deepfake detection and multimedia forensics;
  4. Presentation attack detection and anti-spoofing strategies;
  5. Domain adaptation and generalization in biometric systems;
  6. Self-supervised and few-shot learning for identity recognition;
  7. Edge AI for real-time biometric applications;
  8. Explainable AI in high-stakes biometric and forensic decision-making;
  9. Privacy-preserving biometric learning (e.g., federated learning, differential privacy);
  10. Gait and behavior analysis in surveillance scenarios;
  11. Biometric template protection and secure identity matching;
  12. Fairness, bias mitigation, and ethical aspects of biometric AI.

BioRG is part of the Image Processing LABoratory (IPLAB), that actively collaborates with academic institutions, industry partners, and public agencies to translate foundational research into deployable technologies. Through these synergies, the group contributes to applied innovation, supports the training of Ph.D. candidates, and promotes the development of AI systems that are secure, trustworthy, and human-centric.