Keynote speakers from: 2024 | 2023 | 2022 | 2021 | 2020 | 2019 | 2018 | 2017 | 2016 | 2015 | 2014 | 2013 | 2012 | 2011
Sherin Moussa
Professor, Director of Research, Head of Computer Engineering Department, Université Française d'Égypte
Keynote on: Zero-trust management using AI: Untrusting the trusted accounts in social media
View Abstract
Biography: Sherin Moussa had her PhD degree in conjunction of Ain Shams University, Egypt, with University of Illinois, Urbana-Champaign, USA in 2010. She has +25 years of experience in IT multiple / complex national / regional projects. Prof. Moussa is a consultant to many organizations, with industrial experience in diverse domains. Her research interests include Artificial Intelligence, Internet of Things, Service-oriented Computing, Big Data Analytics, Software Engineering, Bioinformatics, and Data Privacy Preservation and Publishing. She is the Founder and Executive Director of Next Generation Scholar (NGS) research group, Co-organizer of several international workshops and conferences, as well as Guest Editor and Recognized Reviewer at many reputable journals. She was previously the Director of the Quality and Accreditation Unit at Faculty of Computer and Information Sciences, and Director of Grants and International Collaboration Office at Ain Shams University.
Saman Halgamuge
Professor, Department of Mechanical Engineering, School of Electrical, Mechanical and Infrastructure Engineering, University of Melbourne, Australia
Keynote on: New Research in Explainable AI and its application in Health
View Abstract
Biography: Prof Saman Halgamuge, Fellow of IEEE, IET, AAIA and NASSL received the B.Sc. Engineering degree in Electronics and Telecommunication from the University of Moratuwa, Sri Lanka, and the Dipl.-Ing and Ph.D. degrees in data engineering from the Technical University of Darmstadt, Germany. He is currently a Professor of the Department of Mechanical Engineering of the School of Electrical Mechanical and Infrastructure Engineering, The University of Melbourne and the visiting Deputy Vice Chancellor (Research and International) of SLIIT. He is listed as a top 2% most cited researcher for AI and Image Processing in the Stanford database. He is currently a Distinguished Visitor of IEEE Computer Society. He was a distinguished Lecturer of IEEE Computational Intelligence Society (2018-21). He supervised 50 PhD students and 16 postdocs on AI and applications in Australia to completion. His research is funded by Australian Research Council, National Health and Medical Research Council, US DoD Biomedical Research program and international industry. His previous leadership roles include Head, School of Engineering at Australian National University and Associate Dean of the Engineering and IT Faculty of University of Melbourne. His publications can be viewed at Google Scholar.
Yassine Meraihi
Professor, University of Boumerdes, Algeria
Keynote on: Metaheuristics: Recent trends and applications
View Abstract
Biography: Yassine Meraihi received the Ph.D. degree from the University of M’Hamed Bougara Boumerdes, Algeria, in 2017. He is currently a Professor with the University of Boumerdes, Algeria. He is a Deputy Director at the Electrical and Electronic Engineering Institute, University of Boumerdes. He is listed as a top 2% most cited researcher in the Stanford databasein 2024.His research interests include QoS for wireless networks, routing in challenged networks (WMSNs/VANETs),unmanned aerial vehicles, path planning,visible light communication, optical wireless communication,and applications of meta-heuristics to optimization problems.
Zero-trust management using AI: Untrusting the trusted accounts in social media
Sherin Moussa
Abstract:
Traditional machine learning is generally treated as a black-box optimization problem and does not typically produce interpretations that connect inputs and outputs. I explore explainable AI (XAI) also known as “white-box” deep learning models with the ability to discover interpretable functions or textual explanations. I will also describe new work from our group and others focused on XAI and recent applications of XAI.
Active Segmentation: Differential Geometry meets Machine Learning
Saman Halgamuge
Abstract:
Traditional machine learning is generally treated as a black-box optimization problem and does not typically produce interpretations that connect inputs and outputs. I explore explainable AI (XAI) also known as “white-box” deep learning models with the ability to discover interpretable functions or textual explanations. I will also describe new work from our group and others focused on XAI and recent applications of XAI.
Metaheuristics: Recent trends and applications
Yassine Meraihi
Abstract:
Meta-heuristics represent a new generation of powerful approached optimization methods, adaptable and applicable to a large class of problems. They allow us to provide good quality of feasible solutions in a reasonable time. We distinguish two classes of meta-heuristics: those based on a single solution and those based on a population of solutions. I will discuss and compare some recently developed metaheuristics and their applications in different fields such as real world engineering, computer science, medecine, pharmaceutical industry, and many others. I will present also works of my team applying meta-heuristics to solve some real world porblmes.
