Abstract: World-leading multi-disciplinary research at Edinburgh Napier University in Scotland is pioneering the collaborative development of trustworthy and responsible artificial intelligence (AI) technologies to engineer the next-generation of smart industrial and healthcare systems.

This talk will provide an introduction to these emerging technologies and outline a number of real-world use cases including future research directions and challenges.

Bio:
Amir Hussain obtained his B.Eng (1st Class Honours with distinction) and Ph.D from the University of Strathclyde in Glasgow, UK, in 1992 and 1997 respectively. Following an UK EPSRC funded Postdoctoral Fellowship (1996-98) and Research Lectureship at the University of Dundee, UK (2018-20), he joined the University of Stirling, UK, in 2000 where he was appointed to a Personal Chair in Cognitive Computing in 2012. Since 2018, he has been Director of the Centre of AI and Robotics at Edinburgh Napier University, UK. His research and innovation interests are cross-disciplinary and industry-led, aimed at developing cognitive data science and responsible AI technologies to engineer the smart healthcare and industrial systems of tomorrow. He has co-authored nearly 600 papers including around 300 journal papers (h-index: 71, 22,000+ citations) and 20 Books, and supervised over 40 PhD students. He has led major national and international projects, including as Principal Investigator of the current multi-million pound COG-MHEAR programme (funded under the UK EPSRC Transformative Healthcare Technologies 2050 Call) that aims to develop truly personalised assistive hearing and communication technologies. He is founding Chief Editor of (Springer's) Cognitive Computation journal and Editorial Board member for (Elsevier’s) Information Fusion and various IEEE Transactions. Amongst other distinguished roles, he is an executive committee member of the UK Computing Research Committee (the national expert panel of the IET and BCS for UK computing research). He served as General Chair of the 2020 IEEE WCCI (the world’s largest IEEE technical event on computational intelligence, comprising the flagship IJCNN, IEEE CEC and FUZZ-IEEE) and the 2023 IEEE Smart World Congress (featuring six co-located IEEE Conferences).

Abstract: 6G is the next step in the evolution of mobile communication and will be a key component of the Networked Society. In particular, 5G will accelerate the development of the Virtual world.

To enable connectivity for a wide range of applications and use cases, the capabilities of 6G wireless access must extend far beyond those of previous generations of mobile communications. Examples of these capabilities include ultra high data rates, ultra low latency, ultra-high reliability, energy efficiency and extreme device densities, and will be realized by the development of 5G in combination with new radio-access technologies. Therefore, this talk explains the different key technology components of 6G and from implementation to standardization.

Bio:
Shahid Mumtaz is an IET Fellow, IEEE ComSoc and ACM Distinguished speaker, recipient of IEEE ComSoC Young Researcher Award (2020), IEEE Senior member, founder and EiC of IET “Journal of Quantum communication”, Vice-Chair: Europe/Africa Region- IEEE ComSoc: Green Communications & Computing society and Vice-chair for IEEE standard on P1932.1: Standard for Licensed/Unlicensed Spectrum Interoperability in Wireless Mobile Networks. He has more than 15 years of wireless industry/academic experience. He has received his Master's and Ph.D. degrees in Electrical & Electronic Engineering from Blekinge Institute of Technology, Sweden, and University of Aveiro, Portugal in 2006 and 2011, respectively. From 2002 to 2003, he worked for for Ericsson and Huawei at Research Labs in Sweden. He has been with Instituto de Telecomunicações and Full Professor at NTU. He is the author of 4 technical books, 12 book chapters, 300+ technical papers (180+ Journal/transaction, 100+ conference, 2 IEEE best paper award- in the area of mobile communications with H-index of 65. He had/has supervised/co-supervising several Ph.D. and Master Students. He uses mathematical and system-level tools to model and analyze emerging wireless communication architectures, leading to innovative Master's theoretically optimal new communication techniques. He is working closely with leading R&D groups in the industry to transition these ideas to practice. He secures the funding of around 6M Euro.

Abstract: The phrase "metaverse" refers to a virtual environment where people communicate, collaborate, learn, and live via digital avatars.

The metaverse is frequently portrayed as the Internet's next step in development, the place where people would connect socially, enjoy entertainment, and conduct business in ways that are impossible in the real world. Recent developments in augmented reality, mixed reality, and virtual reality are among the primary technologies that offer genuinely immersive experiences in 3D virtual space. Despite its potential, the metaverse is still in its infancy, and in the not too distant future, no one platform will rule all industries. This tutorial explains how academic institutions can create virtual campuses and the advantages the metaverse can offer the academic community. As a real-world study case, the website UCPverse and intaniaverse.com, a model of a virtual university campus, will be used. This guide will be helpful for individuals who want to build their own metaverse.

Bio:
Seminar Summary: The phrase "metaverse" refers to a virtual environment where people communicate, collaborate, learn, and live via digital avatars. The metaverse is frequently portrayed as the Internet's next step in development, the place where people would connect socially, enjoy entertainment, and conduct business in ways that are impossible in the real world. Recent developments in augmented reality, mixed reality, and virtual reality are among the primary technologies that offer genuinely immersive experiences in 3D virtual space. Despite its potential, the metaverse is still in its infancy, and in the not too distant future, no one platform will rule all industries. This tutorial explains how academic institutions can create virtual campuses and the advantages the metaverse can offer the academic community. As a real-world study case, the website UCPverse and intaniaverse.com, a model of a virtual university campus, will be used. This guide will be helpful for individuals who want to build their own metaverse.

Abstract: A current hard disk drive utilizing a perpendicular recording technique is now reaching its storage capacity at 1 tera bits per square inch (Tb/in2) because of the super-paramagnetic effect.

To get around this limitation, several approaches have been proposed, such as bit-patterned magnetic recording (BPMR), two-dimensional magnetic recording (TDMR), and multi-layer magnetic recording (MLMR). But since BPMR is currently commercially accessible and has a storage capacity of up to 4 Tb/in2, this session will concentrate on it. Nonetheless, this talk concentrates on BPMR because it can now be commercially available and has a storage capacity of up to 4 Tb/in2. This talk will provide a brief overview of the sophisticated signal detection and decoding techniques that can be employed in BPMR, such as 2D modulation coding, multi-head multi-track detection, and Al-based data detection.

Bio:
Dr. Piya Kovintavewat received the B.Eng. summa cum laude from Thammasat University, Thailand (1994), the M.S. degree from Chalmers University of Technology, Sweden (1998), and the Ph.D. degree from Georgia Institute of Technology (2004), all in Electrical Engineering. His thesis work titled "Timing Recovery Based on Per-Survivor Processing" was awarded second prize for new Ph.D. thesis in the field of information technology by the National Research Council of Thailand in 2005. He is currently a Professor in Telecommunication program, Faculty of Science and Technology, Nakhon Pathom Rajabhat University (NPRU), Nakhon Pathom, Thailand. His main research interests include coding and signal processing as applied to digital data storage systems. Prior to working at NPRU, he worked as an engineer at Thai Telephone and Telecommunication company (1994-1997), and as a research assistant at National Electronics and Computer Technology Center (1999), both in Thailand. He also had work experiences with Seagate Technology, Pennsylvania, USA (summers 2001, 2002, and 2004).

Abstract: In the realm of healthcare, the demand for skilled medical professionals in developing economies is at an all-time high, with limited resources and access to quality training programs. This talk explores the transformative potential of Virtual Reality (VR) technology as a powerful tool to bridge the skills gap and upskill medical staff in these resource-constrained settings. The presentation will delve into the multifaceted ways in which VR can revolutionize medical training and education in developing economies.

It will highlight the following key points: 1. Immersive Learning Environments: VR creates realistic, immersive simulations that allow medical professionals to practice surgical procedures, diagnose illnesses, and respond to medical emergencies in a safe and controlled virtual environment. This hands-on experience enhances their clinical skills and decision-making abilities. 2. Accessible and Cost-effective Training: Traditional medical training often requires costly equipment and infrastructure. VR provides an accessible and cost-effective alternative, making it easier for healthcare institutions in developing economies to provide high-quality training to their staff. 3. Continuous Learning and Skill Maintenance: Healthcare is a dynamic field with constantly evolving practices and technologies. VR offers a platform for continuous learning and skill maintenance, enabling medical staff to stay updated with the latest advancements in medicine. 4. Addressing Healthcare Disparities: In regions with limited access to healthcare facilities, VR can extend the reach of medical expertise. Telemedicine and remote consultations facilitated by VR can help provide healthcare services to underserved populations. 5. Assessing Competency: VR allows for the objective assessment of medical staff's competency and skills, ensuring that they meet the necessary standards and certifications. 6. Collaborative Learning: VR fosters collaborative learning experiences, enabling medical professionals to engage in virtual team-based training exercises and share knowledge across geographical boundaries. By harnessing the power of VR technology, developing economies can uplift their healthcare systems and empower medical staff with the skills and knowledge required to meet the healthcare needs of their communities. This talk will explore case studies and examples from around the world to showcase the real-world impact of VR in upskilling medical staff, ultimately contributing to improved healthcare outcomes in developing economies. To get around this limitation, several approaches have been proposed, such as bit-patterned magnetic recording (BPMR), two-dimensional magnetic recording (TDMR), and multi-layer magnetic recording (MLMR). But since BPMR is currently commercially accessible and has a storage capacity of up to 4 Tb/in2, this session will concentrate on it. Nonetheless, this talk concentrates on BPMR because it can now be commercially available and has a storage capacity of up to 4 Tb/in2. This talk will provide a brief overview of the sophisticated signal detection and decoding techniques that can be employed in BPMR, such as 2D modulation coding, multi-head multi-track detection, and Al-based data detection.

Bio:
Dr. Piya Kovintavewat received the B.Eng. summa cum laude from Thammasat University, Thailand (1994), the M.S. degree from Chalmers University of Technology, Sweden (1998), and the Ph.D. degree from Georgia Institute of Technology (2004), all in Electrical Engineering. His thesis work titled "Timing Recovery Based on Per-Survivor Processing" was awarded second prize for new Ph.D. thesis in the field of information technology by the National Research Council of Thailand in 2005. He is currently a Professor in Telecommunication program, Faculty of Science and Technology, Nakhon Pathom Rajabhat University (NPRU), Nakhon Pathom, Thailand. His main research interests include coding and signal processing as applied to digital data storage systems. Prior to working at NPRU, he worked as an engineer at Thai Telephone and Telecommunication company (1994-1997), and as a research assistant at National Electronics and Computer Technology Center (1999), both in Thailand. He also had work experiences with Seagate Technology, Pennsylvania, USA (summers 2001, 2002, and 2004).

Abstract: The global health landscape has been dramatically reshaped by the COVID-19 pandemic. For effective responses in public health, swift and dependable diagnostic instruments are essential. The urgency of the situation necessitates the development of noninvasive, contactless, and cost-effective diagnostic platforms that can cater to diverse healthcare settings.

This research presents a novel platform that leverages the combined potential of Magnetic Respiratory Sensing Technology (MRST) and Machine Learning (ML) to facilitate real-time monitoring and diagnosis of COVID-19, along with other respiratory-related diseases. Specifically, the MRST is adept at capturing and monitoring breathing patterns and respiratory rates, utilizing three distinct breath testing protocols: standard breath, breath-holding, and profound inhalation. To transition from mere data collection to valuable diagnostic conclusions, a range of ML algorithms—including support vector machines, random forest, ensemble models, and deep learning paradigms—were trained and validated using datasets from COVID-19 patients and healthy individuals. This multi-model approach not only bolstered diagnostic robustness and reliability but also ensured adaptability to various healthcare conditions and computational resources. Demonstrating remarkable efficacy, the diagnostic system identified respiratory anomalies linked to COVID-19 with an accuracy rate surpassing 90%. A detailed comparison of the ML models' performance further elucidates the distinct advantages and characteristics of each in the diagnostic procedure.

Bio:
Dang Nguyen, B.S.B.E., received his Bachelor of Science with Honors from the Department of Medical Engineering at the University of South Florida. He currently works as a Clinical Researcher at the Corrigan Minehan Heart Center within Massachusetts General Hospital while participating in the Postgraduate Medical Education Program at Harvard Medical School. He has membership in the Tau Beta Pi engineering honor society, American College of Cardiology, and European Society of Cardiology. His research endeavors cover areas such as sensing technologies, wearable medical devices, telemedicine, and advanced computational approaches including machine learning and deep learning. At The Laboratory for Advanced Materials and Sensors, his role is pivotal in the development of Magnetic Respiratory Sensing Technology (MRST), aiming to provide real-time tracking and diagnostics for COVID-19 and other respiratory diseases. Dang Nguyen has authored over 20 publications and 6 patents, with his work featured in The Lancet, PNAS, and BMJ Oncology, and served as a member of the editorial board and reviewer for numerous peer-reviewed journals.

Abstract: A journey into the realm of Exploring the uncharted territory of AI Virtual Humans, where we delve deep into the forefront of Bio-Inspired Communicative AI and the seamless integration of Large Language Models (LLMs) with advanced Computer Vision. Immerse in the multifaceted applications of AI Virtual Humans and underscore the paramount importance of a human-centered approach while dissecting the profound societal implications and transformative potential of this innovative field.

Dr. Sam Khoze is an AI technologist, roboticist, and researcher. He holds a Doctor of Medicine degree, a Postgraduate in Marketing Analysis from MIT, and a Master’s in Artificial Intelligence. He is known for his cutting-edge research, innovative approaches, and focus on Bio-Inspired Communicative AI. He has developed and designed one of the most intelligent social Robot series in association with Professor Hiroshi Ishiguro’s Department of Systems Innovation in the Graduate School of Engineering Science at Osaka University, and Dr. Firouz Naderi, former director of Solar System Exploration at NASA/JPL. Through his collaboration with the Advanced Telecommunications Research Institute (ATR), Dr. Khoze represents some of the world’s most advanced and intelligent robots, Erica and Alter. He has achieved the distinction of being the first to cast and train Hollywood’s first fully autonomous artificially intelligent entity, in a Motion Picture, as featured by The New York Times.

Abstract: Software reliability has emerged as a critical concern in healthcare systems due to the increasing dependence on technology for patient care, data management, and medical research. Unreliable software can result in not only financial losses but also in risks to patient safety and well-being.

This research aims to examine the relationship between software reliability and healthcare outcomes, focusing on critical applications such as Electronic Health Records (EHR), telemedicine, medical imaging, and life-support systems. We discuss the methodologies employed for ensuring software reliability, including formal verification, fault tolerance, and extensive testing regimes, within the context of healthcare compliance standards like HIPAA and FDA guidelines. Our findings indicate that higher levels of software reliability correlate with improved patient outcomes and reduced medical errors. However, this research also highlights ongoing challenges such as the complexity of healthcare systems, rapid technological advancements, and human-software interaction issues. The study concludes with recommendations for improving software reliability in healthcare, encompassing both technical and policy aspects. Digital twins are extensively used in industrial applications. Businesses increase their productivity by converting their physical assets and processes into digital twin. Digital twin is evolving increasingly promising to accelerate digital transformation at a moderate cost.
Bio:
Noha Hazzazi, Ph.D. is an Assistant Professor in the Department of Electrical Engineering and Computer Science at Howard University’s College of Engineering and Architecture. She is also Co-Director of the Appropriate Technology Center. Broadly, her methodological research focuses on process optimization in healthcare systems, software reliability, software safety and security. Dr. Hazzazi is currently leading a joint effort with Boston University under the auspices of the public interest technology university network (PIT-UN) to advocate public interest considerations in technology policy. She is a member of the Golden Key International Honor Society and Phi Beta Delta honor society and is a recipient of a six-sigma certificate during an internship at Raytheon. Dr. Hazzazi received her Ph.D. in Information Technology from George Mason University in Fairfax, Virginia. She is a member of an underrepresented group and is committed to increasing diversity in the computer sciences. She has been a faculty adviser for the Upsilon Pi Epsilon honor society.

Abstract: Deep learning is widely used in numerous applications ranging from speech recognition, natural language understanding and computer vision etc. No single algorithm paradigm has even been so broadly and successfully used as deep nets. Invited talk will focus on history of deep learning, its applications and research trends.

Bio:
Ayyaz Hussain is currently working as Professor of Computer Science at Quaid-i-Azam University Islamabad. From 2010 to 2020 he was Associate Professor and Chair of the Department of Computer Science & Software Engineering at International Islamic University Islamabad. He worked as Research Professor at Gwangju Institute of Science and Technology South Korea from 2013-2014. During 2000 to 2010 he served as Software Engineer at National Engineering and Scientific Commission. Dr. Hussain received his PhD from National University of Computer and Emerging Sciences (NUCES-FAST) in 2009. His research interests include Image processing, computer vision, machine learning and deep learning. He has published more than 40 journal articles along with number of conference papers. He has supervised more than 10 PhD and 25 MS students.