Andrea Atzori profile photo

Andrea Atzori

Postdoctoral Researcher - Fraunhofer IGD
Face RecognitionBiometricsFairnessDeep LearningComputer Vision

Andrea Atzori is a Postdoctoral Researcher at the Smart Living & Biometric Technologies department in Fraunhofer IGD. His research interests focus on machine learning for computer vision, with particular focus on fairness and responsible use of facial biometric systems (more details can be found here).

He has co-authored papers in top-tier international journals, such as Information Fusion (Elsevier) and IEEE Journal of Selected Topics in Signal Processing. He has given talks, poster presentations, and demonstrations at several conferences and workshops, such as IJCB 2022, IJCB 2023, FG 2024, ECCVW 2024, and ICCVW 2025.

He has been involved in the program committee of major computer vision and biometrics-related conferences, such as ECCVW, WACV, IJCB, FG, BIOSIG, IWBF. He has also served as a reviewer for Q1-level journals, including EURASIP Journal on Image and Video Processing, Multimedia Tools and Applications, Journal of Ambient Intelligence and Humanized Computing, IEEE Transactions on Pattern Analysis and Machine Intelligence, and Pattern Recognition.

He has been part of the local organizing committee of UMAP 2024. He has been co-chairing the ReFIP workshop on responsible face image processing at FG 2024.

He is a member of several associations, including CVPL, AIxIA, GRIN, IEEE, IEEE Biometrics Council, and IEEE Young Professionals.

Experience

Postdoctoral Researcher — Fraunhofer IGD
2025-04-01 – present
Darmstadt, DE
  • Field: Computer Science
Research Internship — University of Ljubljana
2024-01-08 – 2024-04-07
Ljubljana, SI
Research Internship — Fraunhofer IGD
2023-05-01 – 2023-07-31
Darmstadt, DE
Research Fellowship - Safespotter Project — University of Cagliari
2020-02 – 2021-08
  • Field: Computer Science
  • The goal of the project was to build, through a network of surveillance cameras distributed in the city, a system to monitor and identify road anomalies (e.g., jaywalking, wrong-way driving, unauthorized stops, or accidents). Each camera was connected to an AI module (NVIDIA Jetson AGX Xavier) that, through the application of object detection algorithms (YOLO V4) and by analyzing each frame received, informed the municipal police station about anomalies detected in a given area, via a control panel.

Education

Ph.D. in Computer Science — Responsible Face Biometrics — University of Cagliari
2021-10-01 – 2025-02-20
Cagliari, Italy
  • Field: Responsible Face Biometrics
Master's Degree in Computer Science — Computer Science — University of Cagliari
2019-09 – 2021-09-22
Cagliari, IT
  • Field: Computer Science
  • Final grade: 110/110 cum laude
  • Thesis: Accident Event Detection by means of Environmental Audio analysis
Bachelor's Degree in Computer Science — Computer Science — University of Cagliari
2016-10 – 2019-07
Cagliari, IT
  • Field: Computer Science
  • Final grade: 108/110
  • Thesis: Detection, tracking and counting of vehicles for city traffic analysis
High School Diploma — Computer Science — I.T.I.S "Othoca"
2009-09 – 2015-06
Oristano, IT
  • Field: Computer Science
  • Final grade: 72/100