Christian Galea
Dr Ing. Christian Galea received the bachelor’s degree in communications and computer engineering and the master’s degree in telecommunications from the University of Malta in 2012 and 2014, respectively, where he also read for his Ph.D. with the Department of Communications and Computer Engineering within the Faculty of Information and Communication Technology, leading to the dissertation entitled 'Face Photo-Sketch Recognition Using Deeply-Learned and Engineered Features' that was performed in collaboration with the Malta Police Force. A Graphics Processing Unit (GPU) was awarded by NVIDIA Corporation for this research, along with a scholarship from the Malta Government Scholarship Scheme (MGSS). He also obtained an engineering warrant from the Engineering Profession Board in Malta.
Following his undergraduate degree, Dr Ing. Galea joined the University of Malta as a researcher, and later served as a technical demonstrator and teaching assistant for several study units at the Faculty of Information and Communication Technology. After reading for his Ph.D., Dr Ing. Galea became a teacher prior to joining the SIROCCO team at INRIA (Rennes, Bretagne-Atlantique, France) as a post-doctoral researcher in the 3D Point Clouds for Light Fields Processing project (as part of the
ERC Advanced Grant project CLIM). He then joined the University of Malta once again, as a post-doctoral researcher in the
Deep-FIR project, focusing on the super-resolution of face images from cameras with low picture quality (e.g. those obtained from some CCTV cameras).
Dr Ing. Galea has also served as a conference session chair, as a reviewer, and as part of the reviewer board for several publications. He was also awarded a letter of commendation from the Dean of the Faculty of ICT at the University of Malta for the high level attained in his undergraduate thesis that dealt with fingerprint matching, which was also nominated for an award by the Chamber of Engineers.
His research interests are in computer vision and image and video processing, particularly applications related to biometrics, heterogeneous face recognition (particularly face photo-sketch recognition), automobiles and Advanced Driver-Assistance Systems (ADAS) including autonomous driving, health, and objective image/video quality assessment.
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