Keynote Speaker: A. Prof. Nasir Saeed, United Arab Emirates University (UAEU), UAE

Brief Introduction: Nasir Saeed (Senior Member, IEEE) his M.Sc. degree in Satellite Navigation from the Polito di Torino, Italy, in 2012. He received his Ph.D. in Electronics and Communication Engineering from Hanyang University, Seoul, South Korea, in 2015. He was an Assistant Professor with the Department of Electrical Engineering at IQRA National University, Peshawar, from 2015 to 2017. From July 2017 to December 2020, he was a Postdoctoral Research Fellow with the Communication Theory Laboratory at King Abdullah University of Science and Technology (KAUST), KSA. He is currently an Associate Professor with the Department of Electrical and Communication Engineering at United Arab Emirates University (UAEU), Al Ain, UAE. He has published more than 70 international journal and conference articles. He is also a Senior Member of IEEE and Associate Editor of IEEE Wireless Communications Letters. His current research interests include non-conventional communication networks, Heterogenous vertical networks, multi-dimensional signal processing, and localization.

Research Area: Digital Signal Processing, Satellite Communication, RF Engineering

Title: AquaTech Unleashed: Opportunities and Challenges in the Internet of Underwater Things

Abstract: The Internet of Underwater Things technology can be established using various underwater wireless communications technologies, including acoustic, radio frequency (RF), magnetic induction, and optical. Each of these technologies has its pros and cons; for example, acoustic technology reaches longer distances but is bandwidth limited, while underwater optical wireless communications (UOWCs) can support higher data rates at the cost of short ranges. This talk will highlight opportunities and challenges faced by Internet of Underwater Things Technology and present future research directions.

Keynote Speaker: A. Prof. Zeeshan Kaleem, COMSATS University Islamabad, Pakistan

Brief Introduction: Zeeshan Kaleem received his B.S. and M.S. Electronics Engineering from the University of Engineering and Technology (UET), Peshawar and Hanyang University, Korea in 2007 and 2010, respectively. He received his Ph.D. in Electronics Engineering Department from Inha University in 2016. From 2010 to 2012, he was a lecturer at Namal College, Pakistan (an associate college of the University of Bradford, UK). Since March 2016, He is working as an assistant professor in the Electrical and Computer Engineering Department, COMSATS University Islamabad, Wah Campus, Pakistan.

Research Area: Cellular Communicationm Communication Engineering, Telecommunications Engineering

Title: Artificial Intelligence to Detect Radio Frequency Signatures of Drones: State-of-the-art & Research Challenges

Abstract: In the rapidly evolving landscape of drone technology, the utilization of Artificial Intelligence (AI) for detecting radio frequency (RF) signatures emitted by drones has gained significant traction. This keynote presentation dives into the state-of-the-art advancements and persisting research challenges in this domain. The keynote will commence with an exploration of the latest AI-powered techniques that integrate machine learning and deep learning with RF signal processing to achieve accurate and efficient drone detection. However, the journey is accompanied by research challenges that demand attention. The variability in RF signatures due to diverse drone types and communication protocols poses a considerable hurdle. Moreover, the influence of environmental factors on RF propagation necessitates adaptive AI models. Real-time detection capabilities and the ethical implications of widespread drone surveillance form additional dimensions to be addressed. As a keynote speaker, this presentation will unravel these complexities and emphasize the need for adaptable AI models to accommodate evolving drone technology and RF emissions. By outlining the current progress in terms of simulation results and critical research directions, it aims to guide researchers and practitioners toward refining AI-driven RF drone detection systems. Ultimately, the keynote discusses the role of AI in enhancing security and safety in an area dominated by drones.