IEEE HONET - Speakers

University of Doha for Science & Technology, Doha, Qatar | December 03-05, 2024

workshop/symposium speakers

Symposium: Smart Sensing for e-Healthcare Applications using IoT, AI and ML Technologies Title: Role of Artificial Intelligence in Smart Cities and Healthcare
Mohammad Ilyas, Ph.D. Professor, College of Engineering and Computer Science Florida Atlantic University Boca Raton, Florida 33431
Abstract: Information and Communication Technologies (ICT) have seen tremendous advances in recent years. The most visible and impactful among these are Internet of Things (IoT) and Artificial Intelligence (AI). IoT provides an elaborate platform for collecting data from various applications. AI can analyze this data (thanks to the availability of powerful computing environments) and make intelligent decisions. This combination is leading to a rapid development of smart systems. These systems include smart healthcare, smart transportation, smart energy, smart environment, smart agriculture, smart cities and many more.	Dr. Mohammad Ilyas
A smart city can use AI and ICT in many ways to significantly improve the efficiency of its operations and improve the quality of life of its citizens. AI is increasingly becoming involved in our existence. Many see emergence of AI as a revolution that will impact every aspect of our lives. Some see it as an evolution based on the recent advances in hardware/software technologies, powerful computational platforms, and access to massive amount of data collected through pervasive communication networks such as Internet of Things (IoT). Smart cities can use IoT and AI effectively to improve its operations. These initiatives will certainly improve quality of life of our citizens and promote cohesive, connected, healthier, and happier communities. This talk will capture the current state of AI in smart cities and discuss potential AI applications for further development of smart cities with a special focus on healthcare.
Speaker Biography: Dr. Mohammad Ilyas is a Professor in the College of Engineering and Computer Science at Florida Atlantic University, Boca Raton, Florida. He has been with the College since 1983. From 1994 to 2000, he was Chair of the Department of Computer Science and Engineering. He served as Associate Dean for Research for the College from 2002 through 2011, and as Dean of the College from 2011 to 2017. From July 2004 to September 2005, he also served the University as Interim Associate Vice President for Research and Graduate Studies. Dr. Ilyas has earned four academic degrees from four different countries. He received his B.Sc. degree in Electrical Engineering from the University of Engineering and Technology, Lahore, Pakistan, in 1976. From March 1977 to September 1978, he worked for the Water and Power Development Authority, Pakistan. In 1978, he was awarded a scholarship for his graduate studies and he completed his MS degree in Electrical and Electronic Engineering in June 1980 at Shiraz University, Shiraz, Iran. In September 1980, he joined the doctoral program at Queen's University in Kingston, Ontario, Canada. He completed his Ph.D. degree Electrical Engineering in 1983. His doctoral research was about switching and flow control techniques in computer communication networks. In 2015, he earned his second Ph.D. in Educational Leadership – Higher Education, from Florida Atlantic University, Boca Raton, Florida. His doctoral research for his second doctoral degree was about globalization and higher education. Dr. Ilyas has conducted successful research in the field of computer communication networks. His current research interests include wireless sensor networks, Internet of Things, smart systems, healthcare technologies. performance modeling, simulation, and impact of globalization on higher education. He has published one book, 26 handbooks, and over 250 research articles. He has supervised 13 Ph.D. dissertations and 38 M.S. theses to completion. He is currently supervising a group of 11 doctoral students. He has been a consultant to several national and international organizations. Dr. Ilyas is an active participant in several IEEE Technical committees and activities. Dr. Ilyas is a Life Senior Member of IEEE, Fellow of IIIS, and was listed as a Fulbright Specialist from June 2017 to June 2022

Tutorial: State of art tutorial for the design and applications of Soft Robotics
John Nassour, Dr.-Ing. habil. Senior Researcher & Group Leader Soft Robotics, Institute for Cognitive Systems Technical University Munich, Germany
	John Nassour (Dr.-Ing. habil.)

Speaker Biography: John Nassour (Dr.-Ing. habil.) holds a habilitation degree from the Chemnitz University of Technology (TUC) in Germany (2021), and a joint doctoral degree in engineering from the Technical University of Munich (TUM) in Germany and the Versailles University (UVSQ) in France in 2014 and 2012 respectively, a master degree in intelligent and communicating systems from the University of Cergy-Pontoise and the École Nationale Supérieure de l’Électronique et de ses Applications in France (2008). He is currently a senior researcher and a group leader in soft robotics at the Institute for Cognitive Systems at TUM. He is interested in the design and control of soft robots, soft wearable robots for rehabilitation, soft sensors, soft actuators, modeling, control, human-robot interaction, and biologically inspired learning.

Symposium on Smart City and IoT Applications to Urban Mobility (SCIAUM’24) Title: Smart city traffic management research at Fredonia
Junaid Ahmed Zubairi, Ph.D. Chair, Computer & Information Sciences, Geology & Environmental Sciences, Mathematical Sciences, Physics SUNY Distinguished Professor, CIS Department, College of Arts and Sciences, SUNY at Fredonia, Fredonia, NY, USA.
In this talk, we are going to present an overview of the research projects completed and in progress in the smart city and IoT research group at State University of New York at Fredonia. In this group, we have been working on the reactive and proactive traffic congestion mitigation techniques. Using the SSSD shortest path discovery, we proposed an algorithm to provide smart information to the drivers on avoiding congested city streets. Later, we worked to define a hierarchy of intersections in which the major intersections play a vital role in traffic rerouting. Our group has also worked on emergency vehicle rerouting to avoid delays due to congestion. We contacted several State DoT's to discover the shortcomings and issues in traffic monitoring and currently we are working on using the machine learning techniques applied to statistical traffic data for congestion prediction.	Dr. Junaid Zubairi

Speaker Biography: Dr. Junaid Ahmed Zubairi received his BE (Electrical Engineering) from NED University of Engineering, Pakistan and MS and Ph.D. (Computer Engineering) from Syracuse University, USA. He worked in Space Research Commission and then joined various institutions in Pakistan and Malaysia where he was engaged in research and curriculum and lab development. In 1999, he accepted a position in State University of New York at Fredonia where currently he is SUNY Distinguished Professor and department chair in the computer science department. He has won many awards and grants including AURAK Presidential award for exceptional academic service, SUNY Chancellor's award for excellence in research and creative activities, Kasling Memorial Lecture award, SUNY Distinguished Professorship, NSF I-CORPS award ($50k), Malaysian Government IRPA research award ($62k), NSF MACS grant ($400k), multiple SUNY scholarly incentive awards and AURAK UAE grant. His research interests include network traffic engineering, network applications and smart city and IoT applications. He has edited two books on network applications and security and has numerous peer reviewed publications including book chapters, journal articles and papers in conference proceedings. He can be reached at zubairi at fredonia.edu.

Symposium on Smart City and IoT Applications to Urban Mobility (SCIAUM’24) Title: A Design Architecture for Steering an Autonomous All-Terrain Vehicle Using Object Tracking via Computer Vision and YOLOv8
James M. Conrad, Ph.D. Professor and Associate Chair Dept. of Electrical and Computer Engineering UNC Charlotte, 9201 University City Blvd, Charlotte, NC
Authors: Joseph M Phillips, Sam Shue and James M. Conrad (University of North Carolina at Charlotte, USA) Many consider autonomous vehicles one of the most promised technologies that have still not yet been widely delivered. While this may be true of automobiles and robo-taxis, much work in autonomous navigation has been accomplished in the realm of farm equipment and construction equipment. Nonetheless, all of these implementations rely on maps, GPS and other technologies (LIDAR, Camera) for localization and obstacle avoidance, but they typically do not build their own maps. Therefore, in GPS-denied environments, they are often “driving blind”. Dr. Conrad’s research concentrates on off-road vehicles. He and his team use LIDAR and camera data to assist in navigation in GPS-denied environments, particularly in forest environments. He will present information about how his research team has created an inexpensive system using an All-terrain Vehicle (ATV) that can autonomously drive in a forest. He will also present on the technology his team has developed to allow an ATV to follow people or vehicles in any environment. This research also extends to the use of the technology to allow a quadrotor to follow an ATV.	Dr. James M. Conrad

Speaker Biography: James M. Conrad received his bachelor's degree in computer science from the University of Illinois, Urbana, and his master's and doctorate degrees in computer engineering from North Carolina State University. He is currently a professor at the University of North Carolina at Charlotte. He also serves as the ECE Department Associate Chair for Computer Engineering and Undergraduate Director. He has served as an assistant professor at the University of Arkansas and as an instructor at North Carolina State University. He has also worked at IBM, Ericsson/Sony Ericsson, and BPM Technology. Dr. Conrad is a Professional Engineer, a Senior Member of the IEEE and a Certified Project Management Professional (PMP). He served on the IEEE Board of Directors as Region 3 director for 2016-2017, and again as a director in 2020 when he also served as IEEE-USA President. He also served as IEEE-Eta Kappa Nu Honor Society President in 2022. He is the author of numerous books, book chapters, journal articles, and conference papers in the areas of embedded systems, robotics, parallel processing, and engineering education.

Workshop on Secure and Efficient AI on the Edge Title: Enabling the Future of Edge AI: Scalable, Personalized, and Secure Intelligence at the Network Edge
Mohamed Abdallah, Ph.D. Professor and Associate Dean of Undergraduate Studies and Quality Assurance Chair of Computer Engineering Program College of Science and Engineering Hamad bin Khalifa University, Qatar
Edge Artificial Intelligence (Edge AI) is reshaping how intelligent systems operate by bringing computation closer to the data source where it is generated to reduce latency and lower operational costs. This decentralized approach is essential for applications such as healthcare, smart cities, and autonomous systems. However, the full potential of Edge AI is hindered by several challenges, including limited and heterogeneous resources, varying data distributions, and increasing security risks. Addressing these challenges requires adaptable, tailored, and scalable solutions for efficient AI model deployment. In this talk, we will begin by demonstrating the critical need for customization in Edge AI, where devices have widely varying computational capabilities. Techniques such as knowledge distillation and resource-aware model pruning allow models to dynamically scale and optimize performance to match available resources, ensuring that even resource-constrained devices can run advanced AI tasks seamlessly. However, customization alone is not enough, as the challenge of data heterogeneity, where data distributions vary across devices, demands an additional layer of personalization.	Dr. Mohamed Abdallah
To fully optimize Edge AI, models must scale to match device resources through customization while adapting to the unique data characteristics of each environment. Therefore, we will explore how personalized models can be developed using clustered learning, which groups devices with similar data profiles to tailor models to the specific characteristics of each cluster. This ensures that models remain effective and relevant across diverse edge environments. Building on this foundation, we will introduce generative AI, particularly large language models (LLMs), and explore how customization and personalization can enable the deployment of lightweight LLMs at the edge. We will explain how the complexity of these models can be adjusted based on resource availability, allowing them to perform advanced tasks. Additionally, we will demonstrate how multi-agent LLMs can work across distributed edge networks, enabling more complex and context-aware applications without overwhelming the limited infrastructure. Finally, as models are personalized and customized across heterogeneous edge environments, security becomes crucial as the decentralized nature of Edge AI makes it vulnerable to adversarial attacks and malicious participants. We will discuss advanced detection mechanisms and trust-based systems to ensure the robustness and reliability of these models.
Speaker Biography: Dr. Abdallah received his B.Sc. degree from Cairo University in 1996, followed by M.Sc. and Ph.D. degrees from the University of Maryland at College Park in 2001 and 2006, respectively. Between 2006 and 2016, he held academic and research positions at Cairo University and Texas A&M University at Qatar. Currently, he is a founding faculty member and Professor at the College of Science and Engineering, Hamad bin Khalifa University (HBKU). Dr. Abdallah's research focuses on AI for wireless networks, wireless security, smart grids, Electric Vehicles, and Blockchain applications for emerging networks. He has authored over 250 peer-reviewed journal and conference papers, contributed to four book chapters, and co-invented four patents. His work has earned him several accolades, including the Research Fellow Excellence Award at Texas A&M University at Qatar (2016), and best paper awards at IEEE conferences such as BlackSeaCom 2019 and the IEEE First Workshop on Smart Grid and Renewable Energy (2015). Additionally, he was awarded the Nortel Networks Industrial Fellowship for five consecutive years (1999-2003). Dr. Abdallah is actively involved in professional service as an associate editor for IEEE Transactions on Communicationsand the IEEE Open Access Journal of Communications. He has served in leadership roles such as Track Co-Chair of IEEE VTC Fall 2019 and Technical Program Chair of the 10th International Conference on Cognitive Radio Oriented Wireless Networks, and has contributed to the technical program committees of numerous major IEEE conferences.

Symposium: Smart Sensing for e-Healthcare Applications using IoT, AI and ML Technologies Title: Fostering Linkage between Medicine, Engineering and Industry for Better Healthcare
Dr. M. Aslam Prof., Fmr. Rector Shifa Medical University, Islamabad, Pakistan
The current presentation is objected to interlink Medicine with Engineering and Industry for innovative and interventional healthcare delivery to improve health for all. The areas of linkage include Biophysics, Bio-mathematics, Biomedical Engineering, Biotechnology, Bionics as Health Technology, Biomedical Instrumentation, Bio-material Sciences, Public Health Engineering, Health Architecting, Genetic medicine and Engineering, Operation Theatre Framing, Development of Movable limbs and joints, Cellular Implants, Human Stents, Health Informatics, Electrophysiology (ECG, EMC, EEG, NCS), Microscopy Analysis, Neural Tissue Engineering, Hospital Consumables Diagnostic Kits, Radiation Oncology, Stem Cell Labs, Artificial skin, Cardiopulmonary Resuscitation Machines, Development of scans CCT, MRI, PET, Nano-biotechnology, Development of Ventilators, Gamma or Caber Knife Surgeries, Robotic Surgeries, Vaccine and Drug Development and Telemedicine	Dr. M Aslam
Transitional medicinal is an inter-disciplinary and trans-disciplinary Science, Doctors, Engineers and Industry together can bring revolution in diagnostics and Therapeutics for better healthcare for the ailing Community.
Speaker Biography: Dr. Muhammad Aslam, MBBS, M.Phil, PhD, FCPS is currently Vice Chancellor of The City University, Islamabad. He is a renowned Professor of Physiology and has been the founding Vice Chancellor of Shifa University. Islamabad and Vice Chancellor, University of Health Sciences (UHS), Lahore, Pakistan. He is the founding President South Asian Association of physiologists (SAAP) and the founding President of Pakistan Association of Medical Editors (PAME). He has nurtured thousands of undergraduates (MBBS/BDS) and dozens of postgraduates including PhD, FCPS and M.Phil. in Physiology.

Symposium: Smart Sensing for e-Healthcare Applications using IoT, AI and ML Technologies Title: Artificial Intelligence (AI) and Society: Navigating the Intended and Unintended Consequences & Social and Ethical Implications
Ahmed S. Khan, Ph.D. Professor of Electrical Engineering Fulbright Specialist Scholar Ex. Dean of the College of Engineering & Information Sciences DeVry University, Addison, Illinois, IL 60101, USA
Emerging technologies of the 4th Industrial Revolution (4IR) are dramatically changing society in the ways we live, work, interact with others, and educate our students. These changes are enabled by such emerging technologies as Artificial Intelligence (AI), Big Data, Internet of Things (IoT), Augmented Reality, Blockchain, Robotics, Drones, Nanotechnologies, Genomics and Gene Editing, Quantum Computing, and Smart Manufacturing. The interplay of these technologies is impacting all sectors across the globe at unprecedented speed, and the time needed to remake the world is getting shorter (less than a year) in contrast to previous industrial revolutions — (1) Steam- and water-powered mechanization (centuries), (2) mass production and electrical power (multiple decades), and (3) Electronics and IT (decades).	Ahmed S. Khan
Among these emerging technologies, Artificial Intelligence (AI) is becoming the most transformative technology in the history of humankind. The stakeholders, policy shapers, and decision makers of the present and future need to be educated not only about AI’s technical capabilities, but also about its social and ethical implications and its intended and unintended consequences, so that they can guide society to its appropriate applications, alert society to its failures, and provide a vision to society in helping to solve its associated challenges and issues in a wise and humane manner. The talk will explore AI’s Intended and Unintended Consequences & Social and Ethical Implications via following critical domains and questions: Ethical Consideration · How to ensure that AI is developed and used ethically with the help of appropriate regulation? · How to deal with AI’s biases and inequalities induced via mathematical models? Privacy and Data Security · How to protect user data and maintain privacy? · What types of regulations are required to ensure privacy and security? Transparency and Accountability · How to ensure AI decision making processes are transparent? · Who is accountable for AI-induced errors? Public Trust and Acceptance · How to develop public trust in AI technologies? · How to educate the public in fostering an informed understanding of AI technologies? Safety and Security · How to ensure that design of AI systems are safe and secure? · How to address the potential risks of autonomous AI technologies? Regulatory and Legal Issues · What legal frameworks are required to govern AI development and deployment? · How to synchronize development of regulations with the swift pace of AI development? Discussion on these critical questions will be helpful in navigating the complexities and challenges of AI adoption — for all stakeholders — in ensuring that its benefits are maximized while minimizing potential risks.
Speaker Biography: Dr. Ahmed S. Khan is a Fulbright Specialist Scholar selected by U.S. Department of State’s Bureau of Educational and Cultural Affairs (ECA).Dr. Khan has more than 40 years of progressively responsible experience in instruction (online and onsite), applied research, curriculum development, program and institutional accreditation (ABET & NCA/HLC), management, and supervision of academic programs at DeVry University. Dr. Khan held many academic positions that include Senior Processor, Chair, and Dean of the College of Engineering & Information, DeVry University, Addison, Illinois, USA. Dr. Khan also served as the National Curriculum Manager at the national headquarters of DeVry University, where he provided leadership by supervising and managing curriculum development and implementation of BSEEt, MSEE & MBA online & onsite programs at 25 DeVry campuses located in the United States and Canada. Dr. Khan received an MSEE from Michigan Technological University, an MBA from Keller Graduate School of Management, and his Ph.D. from Colorado State University. His research interests are in the areas of Nanotechnology, New Teaching & Learning Techniques, and Social and Ethical Implications of Technology. He is the author of many educational papers and presentations. He has authored/co-authored many technical books, including the Science, Technology & Society (STS) series of books (used globally in the academic programs of more than 200 Universities) that include Technology and Society: Issues for the 21st Century & Beyond, and Nanotechnology: Ethical and Social Implications, to stimulate, inspire, and provoke awareness of technology’s impact on society. Dr. Khan is a life senior member of the Institute of Electrical and Electronics Engineering (IEEE), and a life member of American Society of Engineering Education (ASEE). Dr. Khan also served as program evaluator for the accreditation agency ABET.