Prof. Yonghui Li, The University of Sydney, Australia
Speech Title: Beyond 5G towards a Super-connected World
Abstract: Connected smart objects, platforms and environments have been identified as the next big technology development, enabling significant society changes and economic growth. The entire physical world will be connected to the Internet, referred to as Internet of Things (IoT). The intelligent IoT network for automatic interaction and processing between objects and environments will become an inherent part of areas such as electricity, transportation, industrial control, utilities management, healthcare, water resources management and mining. Wireless networks are one of the key enabling technologies of the IoT. They are likely to be universally used for last mile connectivity due to their flexibility, scalability and cost effectiveness. The attributes and traffic models of IoT networks are essentially different from those of conventional communication systems, which are designed to transmit voice, data and multimedia. IoT access networks face many unique challenges that cannot be addressed by existing network protocols; these include support for a truly massive number of devices, the transmission of huge volumes of data burst in large-scale networks over limited bandwidth, and the ability to accommodate diverse traffic patterns and quality of service (QoS) requirements. Some IoT applications have much stringent latency and reliability requirements which cannot be accommodated by existing wireless networks. Addressing these challenges requires the development of new wireless access technologies, underlying network protocols, signal processing techniques and security protocols. In this talk, I will present the IoT network development, architecture, key challenges, requirements, potential solutions and recent research progress in this area, particularly in 5G and beyond 5G.
Biography: Yonghui Li is now a Professor and Director of Wireless Engineering Laboratory in School of Electrical and Information Engineering, University of Sydney. He is the recipient of the Australian Research Council (ARC)Queen Elizabeth II Fellowship in 2008 and ARC Future Fellowship in 2012. He is an IEEE Fellow. His current research interests are in the area of wireless communications. Professor Li was an editor for IEEE transactions on communications, IEEE transactions on vehicular technology and guest editors for several special issues of IEEE journals, such as IEEE JSAC, IEEE IoT Journals, IEEE Communications Magazine. He received the best paper awards from several conferences. He has published one book, more than 300 papers in premier IEEE journals and more than 200 papers in premier IEEE conferences. His publications have been cited more than 20000 times.
Prof. Leopoldo Angrisani,University of Napoli Federico II, Italy
Speech Title: How green is your AI-based measurement?
Abstract: Nowadays, the concept of Sustainability has gained significant relevance across various spheres of human activity, including the realm of Information and Communication Technologies (ICTs). However, ICTs are a double-edge sword for sustainability: they are fundamental tools for developing and implementing more sustainable processes and products; nevertheless, the very use of ICTs has its own environmental impact.
Measurement systems are relevant manifestations of ICTs. Hence, it is extremely important to address the sustainability of measurements and their impact on the environment. In turn, it is also necessary to develop new measurement models that can contribute to a robust assessment of sustainability.
Starting from these considerations, in this talk, an innovative methodological approach aimed at modeling and evaluating the sustainability of ICT manifestations will be presented, with special regard to electronic measurement systems and their evolution towards Cyber-physical Measurement Systems (CPMSs), which holistically integrate measurement solutions with Artificial Intelligence (AI) ones.
Assessing the sustainability of CPMS makes it unavoidable to evaluate the environmental impact of AI-based solutions, due, for example, to the effort required to build large data sets, software libraries, and to train AI models. However, in the literature, there is a lack of systematic studies estimating how much these “actions” can be considered green.
To start bridging this gap, in this talk, also a case study will be introduced, related to the acquisition and processing of biosignals, particularly Electroencephalography (EEG). It will be shown a practical example of optimal balance between the performance of AI-based measurement and the mitigation of the related environmental impact.
Biography: Leopoldo Angrisani is Full Professor of Electrical and Electronic Measurements with the Department of Information Technology and Electrical Engineering of the University of Naples Federico II, Italy. He is also Chair of the Board of the Ph.D. Program ICTH - Information and Communication Technology for Health - and General Manager/Director of CeSMA – Center of Advanced Measurement and Technology Services - of University of Naples Federico II.
His research activity is currently focused on Internet of Things and cyber-physical measurement systems; green soft-growing sensors; measurement sustainability; measurement uncertainty; measurements for Industry 4.0; communication systems and networks test and measurement. He was and is currently involved in many industrial research projects, in cooperation with small, medium and great enterprises, for which he played and is currently playing the role of scientific coordinator. He is currently the Coordinator of the Technical/Scientific Committee of MedITech – one of the eight Italian Competence Centers on I4.0 enabling technologies.
He is Fellow Member of the IEEE Instrumentation and Measurement and Communications Societies, Chair of the IEEE Instrumentation & Measurement Society Italy Chapter, Honorary Chairman of the first (M&N 2019) and second (M&N 2022) edition of the IEEE International Symposium on Measurements & Networking, General Chairman of the second edition (MetroInd4.0&IoT 2019) of the IEEE International Workshop on Metrology for Industry 4.0 and IoT, and General Chairman of the first edition (IEEE MeAVeAS 2023) of the IEEE International Workshop on Measurements and Applications in Veterinary and Animal Sciences. He is vice-chair of the Italian Association “GMEE-Electrical and Electronic Measurements Group”, and corresponding member of the Accademia Pontaniana in Naples, the oldest Italian academy, with almost 600 years of history, which has always brought together renowned Neapolitan scholars. In 2009, he was awarded the IET Communications Premium for the paper entitled “Performance measurement of IEEE 802.11b-based networks affected by narrowband interference through cross-layer measurements” (published in IET Communications, vol. 2, No. 1, January 2008).
The IEEE Instrumentation & Measurement Society Italy Chapter, which he has been chairing since 2015, was awarded in 2016 the prestigious recognition “I&M Society Best Chapter Award” by the IEEE Instrumentation & Measurement Society, in 2017 the prestigious recognition “Most Improved Membership Chapter for 2016” by the IEEE Italy Section, in 2018 the prestigious recognition “Most Innovative Chapter 2018” by the IEEE Italy Section, and in 2021 the prestigious recognition "Chapter of the Year 2021" by the IEEE Region 8 (Europe, Middle Est, Africa).
In 2021, he was awarded the prestigious recognition “2021 IEEE Instrumentation and Measurement Society Technical Award” with the following citation “For contributions in the advancement of innovative methods and techniques for communication systems test and measurement”.
Prof. Reynold Cheng, University of Hong Kong, China
Associate Dean of Engineering in the University of Hong Kong
ACM Distinguished Member
World’s Top 2% Scientists by Stanford University in 2022
2023 AI 2000 Most Influential Scholar Honorable Mention in Database
Speech Title: Data Science for Social Goods: STAR Lab’s Experience
Abstract: In many metropolitan cities, there is a lack of manpower in social care. In Hong Kong, for example, the elderly care homes report a 70% shortage of employees. To alleviate these issues, recently there is a lot of attention on “data science for social goods”, or the use of technologies for enhancing service quality and streamlining administrative work of social workers. In this talk, I will discuss how the HKU STAR (Social Technology And Research) Lab uses data science technologies to support elderly and family care services. I will first introduce HINCare, a software platform that provides volunteering and cultivating mutual-help culture in the community. HINCare uses the HIN (Heterogeneous Information Network) to recommend helpers to elders or other service recipients, and is now supporting 14 NGOs and 7,000 users. I will also discuss our collaboration with the Hong Kong Jockey Club Charities Trust for developing a novel case management and data analysis system for 40% of the family care centers in Hong Kong. These projects have received an HKICT Award, Asia Smart App Awards, and HKU Faculty Knowledge Exchange Awards.
Biography: Professor Reynold Cheng is a Professor of the Department of Computer Science, an Associate Dean of Engineering, and an Associate Director of the Musketeers Foundation Institute of Data Science in the University of Hong Kong (HKU). His research interests are in data science, big graph analytics and uncertain data management. He was the Assistant Professor in the Department of Computing of the Hong Kong Polytechnic University (HKPU) from 2005 to 2008. He received his BEng (Computer Engineering) in 1998, and MPhil (Computer Science and Information Systems) in 2000 from HKU. He then obtained his MSc and PhD degrees from Department of Computer Science of Purdue University in 2003 and 2005.
Professor Cheng is listed as the World’s Top 2% Scientists by Stanford University in 2022, and is named the 2023 AI 2000 Most Influential Scholar Honorable Mention in Database. He received the SIGMOD Research Highlights Reward 2020, HKICT Awards 2021, and HKU Knowledge Exchange Award (Engineering) 2021. He was granted an Outstanding Young Researcher Award 2011-12 by HKU. He received the Universitas 21 Fellowship in 2011, and two Performance Awards from HKPU Computing in 2006 and 2007. He is an academic advisor to the College of Professional and Continuing Education of HKPU. He is a member of IEEE, ACM, ACM SIGMOD, and UPE. He was a PC co-chair of IEEE ICDE 2021, and has been serving on the program committees and review panels for leading database conferences and journals like SIGMOD, VLDB, ICDE, KDD, IJCAI, AAAI, and TODS. He is on the editorial board of KAIS, IS and DAPD, and was a former editorial board member of TKDE.