Luca GUARNERA

Fixed-term Assistant Professor (RTDA) of Informatics [INFO-01/A]

Luca Guarnera was born in Catania on October 26, 1992. Since Jenuary 1, 2022, he is a research fellow in Computer Science at the University of Catania.
He graduated as Ph.D. in Computer Science (XXXIII cycle, PON number E37H18000330006) on October 14, 2021, discussing the thesis entitled “Discovering Fingerprints for Deepfake Detection and Multimedia-Enhanced Forensic Investigations” at the Department of Mathematics and Computer Science, University of Catania. Part of the Ph.D. research was carried out at the University of Hertfordshire, College Lane Campus, Hatfield, UK, under the supervision of Prof. Salvatore Livatino, working on the creation of a software for forensic ballistics analysis and firearms comparison, through the use of the Oculus Rift S headset. He received his MSc (cum laude) in Computer Science from the Department of Mathematics and Computer Science, University of Catania in 2017. He joined IPLab in 2015. In 2017 and 2019, he took part in two Mohamed Bin Zayed International Robotics Challenge (MBZIRC) international robotics competitions. He also participated to four editions (2016-2017-2018-2019) of International Computer Vision Summer School (ICVSS), one edition (2018) of Medical Imaging Summer School (MISS), one edition (2018) of Summer School on Signal Processing (S3P). His main research interests are Computer Vision, Machine Learning, Multimedia Forensics and its related fields with a focus on the Deepfake phenomenon.

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VIEW THE COURSES FROM THE A.Y. 2022/2023 TO THE PRESENT

Academic Year 2021/2022

Research activity involves Computer Vision, Machine Learning, Deep Learning, and, in particular, Digital Forensics (https://iplab.dmi.unict.it/mfs/) with a focus on creating algorithms for:

  • Algorithms to define the authenticity and integrity of mulitmedia content;
  • Forensic Ballistics of multimedia content;
  • Forensic Firearms Ballistics  (https://iplab.dmi.unict.it/mfs/Forensic-Firearms-Ballistics-VR/);
  • Deepfake detection algorithms on digital images, videos and audio (https://iplab.dmi.unict.it/mfs/Deepfakes/);
  • Deepfake creation algorithms (Autoencoder, Generative Adversarial Networks, Diffusion Model).