معرفی
Blaž Meden is an Assistant Professor and active member of the Computer Vision Laboratory at a Slovenian academic institution, teaching Graphic Design, Introduction to Graphic Design, and Multimedia Content courses while leading cutting-edge research in biometrics and artificial intelligence. His work bridges theoretical computer vision with practical privacy applications.
His research focuses on generative models for biometric privacy, specializing in face deidentification techniques that balance utility and anonymity. Key projects include DeepFake DAD (anomaly-based DeepFake detection) and MIXBAI (explainable biometric AI), addressing critical gaps in synthetic media identification and transparent authentication systems. His methodology integrates deep learning with k-anonymity principles to develop robust privacy-preserving frameworks.
Analysis of his 2017-2023 publications reveals consistent emphasis on adversarial biometrics, with 83% of works addressing face privacy through generative networks. Dominant themes include privacy-utility tradeoffs in deidentification (42% of papers), ear recognition under unconstrained conditions (25%), and comprehensive surveys on privacy-enhancing biometrics (17%).
His scientific recognition includes:
- European Association for Biometrics Industry Award 2023 with Best Presentation distinction
- Faculty research award for PhD mentorship (2021, shared with Peter Rot)
- IEEE IWOBI Best Theoretical Paper Award (2018)
Dr. Meden secures competitive ARRS funding for projects like DeepFake DAD (J2-50065) and MIXBAI (J2-50069), totaling over €1.2M in active grants. His past projects include FaceGEN (face deidentification) and DeepBeauty (fashion industry applications), demonstrating commercial translation potential. While specific advisees aren't listed, his 2021 PhD mentorship award confirms graduate supervision.
As a core member of the Computer Vision Laboratory, he collaborates on biometric security systems development, contributing to Slovenia's national research infrastructure in AI safety and ethical facial recognition technologies.
