Prof. Fethi Rabhi


Fethi Rabhi is a Professor in the School of Computer Science and Engineering at the University of New South Wales (UNSW) in Australia. He has held important positions in several major research initiatives including Program Manager in the Capital Markets Cooperative Research Centre (CMCRC), Research Leader in a large DEST (part of Australian Government) Innovation Science Linkage grant, and lately Research Leader in the New Financial Services project which was part of Smarts Services Cooperative Research Centre. He also initiated several collaboration links in the area of financial data analysis with Universities and companies worldwide (e.g. UK, Germany, UAE, Qatar, Turkey and Malaysia). On the education side, he contributed to bridging the knowledge gap between Computer Science and Finance. In November 2022, he co-founded the Fintech AI Innovation Consortium (FAIC), a new initiative that builds on UNSW’s strength in digital innovation technologies and AI applications and is driven by both the Engineering and Business faculties. 

Prof. Soufiene Djahel


Soufiene Djahel is a Reader in Connected and Autonomous Systems at the University of Huddersfield (UK) and a Visiting Associate Professor in the School of Computer Science at University College Dublin (Ireland). He was the founding head of the Smart and Sustainable Cities (S2C) lab within the department of computing and mathematics at Manchester Met Univ. from 2017 until August 2022. Dr. Djahel earned his PhD in wireless networks security from Lille 1 University of Science and Technology in 2010. He published more than 70 peer-reviewed research articles in international journals and conferences on wireless networks, network security, IoT, intelligent transportation systems, CAVs and UAVs. He supervised to successful completion 7 Ph.D. students and 28 Master students, and currently supervising 5 Ph.D. students. His research was supported by Newton Mosharrafa Fund, JSPS, IntelliCentrics UK LTD, EPSRC DTP and the Transport Systems Catapult. He served as Senior Lecturer at MMU (UK); Engineering Research Manager at University College Dublin (IE); Postdoctoral Fellow at ENSIEE (FR); Associate Lecturer and Researcher at Lille 1 University of Science and Technology (FR); and Teaching Assistant at IMT Nord Europe (FR). He is fellow of the Higher Education Academy in the UK, member of EPSRC peer review college and the Vice-Chair of the IEEE TCGCC SIG on Green Internet of Vehicles. Dr. Djahel is regularly invited to undertake different leadership roles in several IEEE sponsored international conferences; and served as expert reviewer for three European research councils. He is also the recipient of the FY2021 JSPS Invitational Fellowship for Research in Japan award from the Japan Society for the Promotion of Science.

Prof. Abdelouahab Moussaoui


Abdelouahab Moussaoui is a teacher/researcher at Ferhat Abbas Sétif 1 University in Sétif, Algeria, where he obtained the rank of Full Professor in 2011. He earned his degree in computer engineering in 1991 from the Department of Computer Science at the University of Houari Boumediene’s Sciences and Technology (USTHB) in Algeria. He also received a Master’s degree in aerospace engineering in 1992 from the University of Sciences and Technology in Oran (USTO). In 1995, he earned a Master’s degree in artificial intelligence from the University of Sidi Belabbes, Algeria, and a Ph.D. in artificial intelligence and medical imaging from Ferhat Abbas University, Algeria, in 2005, where he attained the status of Full Professor in computer science. He is referenced in several renowned international journals such as Springer and Elsevier. His research focuses on the fields of machine learning, deep learning, clustering algorithms, and applications of multivariate image classification in biological and medical domains. He has published a substantial number of scientific articles, participated in numerous seminars and scientific conferences as a reviewer, and supervised many doctoral theses in the field of supervised and unsupervised deep learning applied to the biomedical field (medicine and biology). He has also worked extensively on pattern recognition algorithms, complex data exploration, physiological signal analysis, and bioinformatics. In his current work, Professor Abdelouahab Moussaoui is interested in self-supervised learning techniques, representation learning, as well as semantic image segmentation techniques through visualization and interpretability techniques for convolutional neural networks in deep learning (CAM, Grad-CAM, CBAM, etc.). He currently chairs a national committee for the development of a national artificial intelligence program, which will be taught as a subject of study for new doctoral students.