Abstract:

Bio: Ernesto Damiani is Full Professor at Università degli Studi di Milano, Director of Center for Cyber Physical Systems (C2PS) within the Khalifa University, leader of the Big Data area at Etisalat British Telecom Innovation Center, and President of the Consortium of Italian Computer Science Universities (CINI). He is also part of the ENISA Ad-Hoc Working Group on Artificial Intelligence Cybersecurity, where he serves as Rapporteur.

According to DBLP (January 2021), Ernesto Damiani has authored 137 journal papers, 336 refereed articles in proceedings of international conferences, and published 57 books and chapters as an author or editor. According to Google Scholar, Ernesto's work has been cited more than 18,200 times and his h-index is 57; 291 of his papers have at least 10 citations. On Scopus he has 616 documents and more than 7,100 total citations by more than 5,600 documents. His Scopus h-index is 36. With 542 publications listed on DBLP, he is considered among the most prolific European computer scientists.

His areas of interest include cyber-physical systems, Big Data Analytics, Edge/Cloud security and performance, Artificial Intelligence, and Machine Learning. Ernesto Damiani has pioneered model-driven data analytics. Ernesto has been a recipient of the Stephen Yau Award from the Service Society, of the Outstanding contributions Award from IFIP TC2, of the Chester-Sall Award from IEEE IES, and of a doctorate honoris causa from INSA - Lyon (France) for his contribution to Big Data teaching and research.

Abstract: With the advancement of technology. the need to automatically evaluate the quality of multimedia content whether audio, images, or videos, has become an important part of most multimedia systems based on machine learning and computer vision principles. While current objective multimedia quality metrics have shown high correlation with subjective scores, nevertheless, we still face many challenges. This includes but is not limited to difference in the performance of metrics across various datasets and distortions, dealing with multiple distortions, run-time performance, memory requirements, application-specific metrics, etc. Ensuring and enhancing quality has become a paramount concern. In this talk, we explore the intersection of multimedia content evaluation, advances made in AI/ML, and the transformative capabilities of Generative Artificial Intelligence (AI). The presentation will identify the approaches and tools that are used to gauge the excellence of multimedia content in various media and their forms.

We will start by enumerating the challenges, risks and difficulties of standard multimedia ratings in present-day society due to the fact that in the evaluation, each multimedia representation almost touches on elements of visual aesthetic perception of the images, the sound, animations, difficultly/ ease in comprehension and user interactivity. We underline that this more contextual understanding of multimedia is unrevealed in traditional evaluation procedures.

The talk then shifts focus to the promising role of Generative AI tools in overcoming these challenges. We provide an overview of the latest advancements in models, such as Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs). Lastly, the presentation concludes with a forward-looking perspective, addressing ethical considerations, and future directions in the relationship between multimedia content evaluation and AI and generative AI. The goal is to present a roadmap for unlocking the potential of AI and generative AI in enhancing QoE evaluation tools and in offering valuable insights for industry professionals, researchers, and enthusiasts.

Bio: Mohamed Deriche received his B.Sc. degree in electrical engineering from the National Polytechnic School, Algeria, and his Ph.D. degree in signal processing from the University of Minnesota in 1994. He worked at Queensland University of Technology, Australia, before joining King Fahd University of Petroleum and Minerals (KFUPM) in Dhahran, Saudi Arabia, where he led the signal processing group. He has published more than 300 papers in multimedia signal and image processing. In 2021, he joined Ajman University to promote the AIRC centre and the new Masters in AI within the College of Eng and IT. He delivered numerous invited talks and chaired several conferences including GlobalSIP-MPSP, IEEE Gulf (GCC), Image Processing Tools and Applications, and TENCON (a Region 10 conference). He has supervised more than 50 M.Sc. and Ph.D. students and is the recipient of the IEEE Third Millennium Medal. He also received the Shauman Best Researcher Award, and both the Excellence in Research and Excellence in Teaching Awards while at KFUPM and at Ajman University. He is ranked in the top 0.5% scientists according the GPS Scholar ranking and in the top 80 achieved scientists in UAE. His research interests cover signal and image processing spanning from theory to models to diverse applications in multimedia, biomedical, seismics, to language processing.

Abstract: As artificial intelligence continues to evolve, so too do the discussions around its societal impact, ethical implications, and the ways it can both benefit and challenge humanity. This panel, titled "The Future of AI: Navigating Benefits, Risks, and Ethical Dilemmas," brings together experts from diverse backgrounds to explore the promises and pitfalls of AI. Panelists will discuss the transformative potential of AI across sectors like healthcare, transportation, and energy, while addressing concerns about transparency, accountability, and human rights. The session will delve into the ethical questions AI raises, such as issues of bias, privacy, and decision-making autonomy, as well as the role of policy and regulatory frameworks in mitigating risks. Join us for a thoughtful discussion on creating a balanced and responsible future for AI that serves the common good.

Abstract: Visible Light Communication (VLC) is based on the principle of modulating the intensity of light-emitting diodes (LEDs) to enable high data rate transmission over the unregulated optical spectrum. It is considered a powerful complement to radio frequency-based solutions in dense user environments and a viable alternative in locations where radio waves may be restricted or prohibited. In this talk, we will first provide an overview of this promising technology, highlighting its unique advantages and potential applications. We will then explain how VLC channels can be realistically modeled and introduce key physical layer technologies that enable the development of high-speed VLC systems. Although first-generation VLC modems have successfully demonstrated the feasibility of indoor light-based wireless networks, significant advancements are still needed to position VLC as an integral part of 6G and beyond networks. Toward this direction, we will discuss the current challenges and future research directions.

Bio: Murat Uysal received BSc and MSc degrees in electronics and communication engineering from Istanbul Technical University, Turkey, in 1995 and 1998, respectively, and his PhD degree in electrical engineering from Texas A&M University, College Station, USA, in 2001. Dr. Uysal began his academic career as an Assistant Professor at the University of Waterloo, Canada in 2002 and was promoted to Associate Professor with tenure in 2007. In 2011, he joined Ozyegin University, Turkey where he served as the Department Chair of Electrical and Electronics Engineering and the Founding Director of Center of Excellence in Optical Wireless Communication Technologies (OKATEM). In September 2023, he joined New York University Abu Dhabi as a Professor of Electrical Engineering. Dr. Uysal's research interests are in the broad area of communication theory with a particular emphasis on the physical layer aspects of wireless communication systems in radio and optical frequency bands. On these topics, he has authored some 450 journal and conference papers and received more than 22.000 citations with an h-index of 66. Uysal is an IEEE Fellow and the former Chair of the IEEE Turkey Section. He currently serves as an Area Editor for IEEE Transactions on Communications. Previously, he served as an Editor for IEEE Transactions on Communications, IEEE Transactions on Wireless Communications, IEEE Transactions on Vehicular Technology, and IEEE Communications Letters. He was involved in the organization of several IEEE conferences at various levels. In particular, he served as the Technical Program Committee Chair of major IEEE conferences, including WCNC 2014, PIMRC 2019, and VTC-Fall 2019. Between 2011 and 2015, he was the Chair of EU COST Action OPTICWISE, a high-profile consolidated European scientific platform that brought together more than 150 researchers in the research area of optical wireless communication. Dr. Uysal's major distinctions include NSERC Discovery Accelerator Award in 2008, University of Waterloo Engineering Research Excellence Award in 2010, Turkish Academy of Sciences Distinguished Young Scientist Award in 2011, Ozyegin University Outstanding Researcher Award in 2014, National Instruments Engineering Impact Award in 2017, Elginkan Foundation Technology Award in 2018, IEEE Communications Society Best Survey Paper Award in 2019, IEEE Turkey Section Outstanding Service Award in 2021, Mustafa Prize and Tubitak Science Award in 2023.

Abstract: Dual-function radar-communication (DFRC) systems are integrated sensing-communication systems that use the same waveform for simultaneously probing the surroundings and communicating with other equipment. DFRC systems offer high spectral, hardware, and power efficiency, and as such are prime candidates for 6G wireless systems. Before the DFRC promise is realized, several issues need to be addressed. One of those issues is security. By embedding communication information in the probing waveform, DFRC systems are vulnerable to eavesdropping by the targets. In this talk, we will present a novel physical layer security (PLS) system design for optimizing the communication secrecy rate while maintaining sufficient power in the target echoes to ensure high target sensing performance. We will also present a novel Directional Modulation approach for achieving PLS via Time Modulated arrays, via which, the DFRC system is designed to deliver the signal intact to the legitimate destination and scrambled in all other directions. We will examine the possibility of the target/eavesdropper defying the proposed security measures and investigate additional protection measures.

Bio: Athina P. Petropulu is a distinguished Professor at the Electrical and Computer Engineering (ECE) Department at Rutgers, having served as chair of the department during 2010-2016. Prior to joining Rutgers, she was a Professor of ECE at Drexel University (1992-2010). She held Visiting Scholar appointments at SUPELEC, Universite' Paris Sud, Princeton University, and University of Southern California. Dr. Petropulu's research interests span statistical signal processing, wireless communications, signal processing in networking, physical layer security, and radar signal processing. Dr. Petropulu is a Fellow of IEEE and the American Association for the Advancement of Science (AAAS), and recipient of the 1995 Presidential Faculty Fellow Award given by the US National Science Foundation and the White House. She has played key roles in her professional society, including serving as 2022-2023 President of the IEEE Signal Processing Society, Editor-in-Chief of the IEEE Transactions on Signal Processing (2009-2011), and IEEE Signal Processing Society Vice President-Conferences (2006-2008). She was Technical Program Co-Chair of the 2023 IEEE ICASSP, General Co-Chair of the 2018 IEEE SPAWC, and General Chair of the 2005 ICASSP. She was a Distinguished Lecturer for the Signal Processing Society and the IEEE Aerospace & Electronics Systems Society. For her service, Dr. Petropulu has received the 2012 IEEE Signal Processing Society Meritorious Service Award. She is also co-recipient of the 2005 IEEE Signal Processing Magazine Best Paper Award, the 2020 IEEE Signal Processing Society Young Author Best Paper Award (B. Li), the 2021 IEEE Signal Processing Society Young Author Best Paper Award (F. Liu), the 2021 Barry Carlton Best Paper Award by IEEE Aerospace and Electronic Systems Society, and the 2023 Stephen O. Rice Prize Best Paper Award by the IEEE Communications Society.

Artificial intelligence (AI) is rapidly becoming a critical component in many engineering systems and disciplines today. In the field of wireless technology, AI is being utilized to design and develop smarter methods for modeling physical layers, optimizing the performance of wireless systems and networks, and addressing new 6G design challenges. In this hands-on workshop, you will write and run code entirely in the browser using MATLAB® Online™. You will learn how to apply AI principles (including machine learning, deep learning, and domain-specific processing) to wireless communication workflows.

This interactive session will include:

Familiarizing yourself with MATLAB Online and AI tools. Creating and evaluating necessary components for successful AI modeling by implementing an example of Modulation Classification. Diving deep into an advanced, domain-specific application that showcases a complete workflow for accomplishing 5G Channel Estimation.

Abstract: Join a former Navy Chief Cyber Technician as he unveils captivating stories of cyber intrigue and high-stakes operations. From daring strikes on military assets to covert data theft and threats to critical industries like oil and business, these accounts shed light on the hidden world of cyber warfare. Dive into the "how" and "why" behind seven legendary cyber incidents, and explore their implications for today's cybersecurity landscape and the future.

Bio: Shane Wegner is a cybersecurity expert with extensive experience in both the US and UAE. He served 10 years in the US Navy as a Chief Cryptologic Technician: Networks, where he led nearly a thousand cyber operations in support of national defense and provided leadership to the 501 Combat Mission Team. After his military service, Shane spent an additional 5 years in the UAE, supporting their cyber missions. Now with Cybergate, he is dedicated to raising cyber awareness and delivering impactful training and education throughout the UAE.

Abstract: Individuals, industry, and government are embracing cyberspace's many advantages. Nevertheless, their increasing reliance on cyber technologies makes them more vulnerable to those who attack digital infrastructure to undermine national security, economic prosperity, and way of life. It is a common scenario that the only piece of evidence of a targeted attack is the malicious executable code itself. Analyzing malicious code (malware) requires reverse engineering, as malware source code is often unavailable. It is important to mention that this task is manually intensive and time-consuming. This opens the following questions: Why was this executable written? Which compiler was used? Which free software packages did the developer use? Which sections of the code were borrowed? Who wrote the executable? These questions are of paramount importance to security analysts and reverse engineers, and binary fingerprinting approaches may provide valuable insights that can help answer them. This talk will present a set of innovative solutions that boost the state of the art. It will address some of the most fundamental problems, notably authorship attribution, reusable code discovery, fingerprinting free open-source software packages, and compiler identification.

Bio: Dr. Saed Alrabaee received a Ph.D. in information system engineering from Concordia University, Montreal, QC, Canada. He is currently an Associate Professor with the Department of Information Systems and Security at United Arab Emirates University (UAEU), Al Ain, United Arab Emirates. He is also the director of the Center for Excellence in Teaching and Learning. He is a permanent research scientist at Canada's National Cyber Forensic and Training Alliance (NCFTA). His research and development activities and interests focus on reverse engineering, including binary authorship attribution, characterization, and malware investigation. In this domain, he has published more than 50 papers in top-tier journals and prestigious conferences.

This workshop on "Research Design and Methods Using AI" will explore the transformative impact of artificial intelligence on contemporary research practices. It will provide an overview of how AI-driven tools and techniques can enhance the design, execution, and analysis phases of research across diverse fields. Participants will learn about the integration of AI in developing research questions, automating data collection, improving data analysis through advanced algorithms, and ensuring robust interpretation of results. Attendees will gain practical insights and strategies for incorporating AI into their research methodologies to achieve more efficient, accurate, and innovative outcomes.

Objectives:

Explore AI integration in formulating research questions, literature reviews and designing methodologies. Demonstrate AI-driven automation of data collection for improved efficiency. Familiarize participants with AI tools for advanced data analysis. Equip researchers with strategies for incorporating AI into diverse research practices.