Keynote Speakers

Emeritus Professor Nikola Kasabov, LFIEEE

School of Engineering, Computing and Mathematical Sciences
Auckland University of Technology
New Zealand

Biography

Professor Nikola (Nik) Kirilov Kasabov (also spelled legally as Kassabov) is Life Fellow of IEEE (Institute for Electrical and Electronic Engineers), Fellow of RSNZ (Royal Society of New Zealand), Fellow of the College of Fellows of INNS (International Neural Network Society), Distinguished Visiting Fellow of the Royal Academy of Engineering UK, Fellow of the NZ IITP (Institute for IT Professionals), Fellow of the Asia-Pacific Artificial Intelligence Association. He is the Founding Director of the Knowledge Engineering and Discovery Research Institute (KEDRI) and Professor Emeritus of Knowledge Engineering in the School of Engineering, Computing and Mathematical Sciences at AUT.

His main interests are in the areas of: computational intelligence; neuro-computing; bioinformatics; neuroinformatics; speech and image processing; data mining; knowledge representation and knowledge discovery.

He has published over 700 works, among them 320 journal papers, 10 text books, edited research books and monographs, conference papers, book chapters, edited conference proceedings, 28 patents and authorship certificates in the area of intelligent systems, neural networks, connectionist and hybrid connectionist systems, fuzzy systems, expert systems, speech and image recognition, neuroinformatics, bioinformatics, neuroengineering. He originated the first neuromorphic spatio-temporal data machine called NeuCube, implemented by his collaborators and used in the labs of 50 countries. He has also been included in the Stanford University's List of the Top 2% Scientists in the World by Citations since 2020.

He held a secondment positions as George Moore Chair/Professor at Ulster University UK (2020-2024) and at IIKT-Bulgarian Academy of Sciences (2022-2025). He has held Honorary and Visiting Professorships at the University of Auckland NZ, Teesside University UK, Shanghai Jiao Tong University, Dalian University and Peking University, China, ETH/UniZurich. He was awarded Doctor Honoris Causa of Obuda University, Hungary.

Professor Kasabov served as the President of the International Neural Network Society (INNS) (2009-2010), Asia-Pacific Neural Network Assembly (APNNA) (2008), Asia Pacific Neural Networks Society (2019) (APNNS).

Professor Kasabov is the Genera co- Chair of IJCNN2023, honorary chair of ICONIP2024 and a General Chair of a series of biannual international conferences on Neurocomputing and Evolving Intelligence in New Zealand. He received numerous awards, including: EU Marie Curie Fellowship (2011-2012); the INNS Ada Lovelace Meritorious Award (2019); the INNS Gabor Award (2012); The Bayer Science Innovator Award NZ (2007); The Royal Society of New Zealand Silver Medal (2001); the AUT Medal (2105); Honorary member of the Bulgarian Informatics Association AOKSIT (2018) and the Greek Computer Society (2014).

Professor Kasabov is the EiC of the Springer-Nature series of Bio-and Neurosystems and the journal Evolving Systems. He has served as Associate Editor of numerous international journals, including Neural Networks, Information Sciences, IEEE TrCDS. He has extensive academic experience at various academic and research organisations: University of Otago, New Zealand; University of Essex, UK; University of Trento, Italy; Technical University of Sofia, Bulgaria; TU Kaiserslautern Germany; ETH Zurich; Shanghai Jiao Tong University; Ulster University UK, Technical University of Sofia. Professor Kasabov has Masters degrees in Computer Science and Engineering, and a PhD in Mathematical Sciences from the Technical University, Sofia, Bulgaria. He has supervised to completion 50+ PhD students.

Professor Kasabov is the Founding Director of Knowledgeengineering.ai. He has been appointed as Advisory Board member of Conscium.com, which is the world’s first applied AI consciousness research organisation with the aim to deepen our understanding of consciousness to pioneer efficient, intelligent, and safe AI that builds a better future for humanity.

Professor Mohamed-Slim Alouini, FIEEE

Al-Khawarzmi Distinguished Professor, Electrical and Computer Engineering
King Abdullah University of Science and Technology
Saudi Arabia.

Title

Towards connecting the remaining 3 billion

Abstract

The transformative influence of Internet and Communication Technology (ICT) has reshaped society, touching every aspect from the economy to healthcare. As the widespread deployment of 5G continues, there is an on-going focus on the inception of the sixth generation (6G) of wireless communication systems (WCSs). Anticipated to shape the future of connectivity in the 2030s, 6G aims to deliver unparalleled communication services to meet the demands of hyper-connectivity.

While densely populated urban areas have traditionally been the primary beneficiaries of WCS advancements, the vision for 6G transcends city limits. Aligned with the United Nations’ sustainability goals for 2030, an important aspect of 6G endeavors to democratize the benefits of ICT, fostering global connectivity sustainably. This talk delves into this particular envisioned landscape of 6G, providing insights into the future of wireless communication and guiding research efforts towards sustainable, inclusive, and high-speed connectivity solutions for the future. Central to this discussion are two emerging technologies: Free Space Optics (FSO) and Non-Terrestrial Networks (NTN). These innovative solutions hold the promise of extending high-speed connectivity beyond urban hubs to underserved regions, fostering digital inclusivity and contributing to the development of remote areas. Through this exploration, we aim to convey the potential of 6G and its role in shaping a connected, sustainable future for all.

Biography

Mohamed-Slim Alouini was born in Tunis, Tunisia. He received the Ph.D. degree in Electrical Engineering from the California Institute of Technology (Caltech) in 1998. He served as a faculty member at the University of Minnesota then in the Texas A&M University at Qatar before joining in 2009 the King Abdullah University of Science and Technology (KAUST) where he is now the Al-Khawarizmi Distinguished Professor of Electrical and Computer Engineering and Holder of the UNESCO Chair on Education to Connect the Unconnected. Prof. Alouini is a Fellow of the IEEE and OPTICA (Formerly the Optical Society of America (OSA)). He is currently particularly interested in addressing the technical challenges associated with the uneven distribution, access to, and use of information and communication technologies in rural, low-income, disaster, and/or hard-to-reach areas.

Prof. Dr. Md. Abdur Razzaque, SMIEEE

Chairman, Department of Computer Science and Engineeering
University of Dhaka,
Bangladesh

Biography

Md. Abdur Razzaque is a Professor of the Dept. of Computer Science and Engineering, University of Dhaka and he is the current chairman of the Department. He chaired 2021 and 2020 Executive Committees for IEEE Computer Society Bangladesh Chapter. He received his BS in Applied Physics and Electronics and MS in Computer Science from University of Dhaka, Bangladesh in 1995 and 1996, respectively. He obtained a PhD in Computer Engineering from Kyung Hee University, South Korea in 2009. He worked for Green University of Bangladesh for different periods as Pro Vice Chancellor, Dean of Faculty of Science and Engineering and Chairperson, Dept of CSE during 2016-2021. He was a research professor at Kyung Hee University, South Korea during 2010-2011. He worked as a visiting professor in Stratford University, Virginia, USA in 2017. He is the director of Green Networking Research Group (http://cse.du.ac.bd/gnr) of the Dept. of CSE, DU. He has been promoting Outcome Based Education for Science and Engineering Faculties of leading universities of the country. He lead many national and international funded research projects. His research interest is in the area of modeling, analysis and optimization of wireless networking protocols and architectures, Mobile Crowdsourcing, Sensor Data Clouds, Internet of Things, Edge Computing, etc. He has published 180+ research papers in peer-reviewed conferences and journals. He is offering editorial services to reputed journals and contributing to numerous international conferences at different capacities. He is a senior member of IEEE, member of IEEE Computer Society, Internet Society (ISOC), etc.

Professor Sozo Inoue, SMIPSJ

Graduate School of Life Science and Systems Engineering
Kyushu Institute of Technology,
Japan

Biography

Sozo Inoue is a full professor in National Kyushu Institute of Technology, Japan, and the Chief Technical Officer of AUTOCARE LLC. His research interests include human activity recognition with smart phones, and healthcare application of web/pervasive/ubiquitous systems. Currently he is working on applications of activity recognition and health forecasting for nursing care and medicine to hospitals and more than 50 nursing facilities using smartphones and IoT. Inoue has a Ph.D of Engineering from Kyushu University in 2003. After completion of his degree, he was appointed as an assistant professor in the Faculty of Information Science and Electrical Engineering at the Kyushu University, Japan. He then moved to the Research Department at the Kyushu University Library in 2006. Since 2009, he has been appointed as an associate professor in the Faculty of Engineering at Kyushu Institute of Technology, Japan, and moved to Graduate School of Life Science and Systems Engineering at Kyushu Institute of Technology in 2018, and appointed as a full professor from 2020 and a head of Care XDX Center in Kyushu Institute of Technology from 2022. Meanwhile, he was a guest professor in Kyushu University, a visiting professor at Karlsruhe Institute of Technology, Germany, in 2014, a special researcher at Institute of Systems, Information Technologies and Nanotechnologies (ISIT) during 2015-2016, and a guest professor at University of Los Andes in Colombia in 2019. He was a technical advisor of Team AIBOD Co. Ltd during 2017-2019, and a guest researcher at RIKEN Center for Advanced Intelligence Project (AIP) during 2017-2019. He was a director during 2020-2021 and is a senior member of the Information Processing Society of Japan (IPSJ), a member of the IEEE Computer Society, the ACM, the Institute of Electronics, Information and Communication Engineers (IEICE), the Japan Society for Fuzzy Theory and Intelligent Informatics, the Japan Association for Medical Informatics (JAMI), and the Database Society of Japan (DBSJ).

Dr. Mohammad Ali Moni

School of Health and Rehabilitation Sciences,
Faculty of Health and Behavioural Sciences
The University of Queensland,
Australia

Biography

Dr Moni holds a PhD in Artificial Intelligence & Data Science in 2014 from the University of Cambridge, UK followed by postdoctoral training at the University of New South Wales, University of Sydney Vice-chancellor fellowship, and Senior Data Scientist at the University of Oxford. Dr Moni then joined UQ in 2021. He also worked as an assistant professor and lecturer in two universities (PUST and JKKNIU) from 2007 to 2011. He is an Artificial Intelligence, Computer Vision & Machine learning, Digital Health Data Science, Health Informatics and Bioinformatics researcher developing interpretable and clinical applicable machine learning and deep learning models to increase the performance and transparency of AI-based automated decision-making systems.

His research interests include quantifying and extracting actionable knowledge from data to solve real-world problems and giving humans explainable AI models through feature visualisation and attribution methods. He has applied these techniques to various multi-disciplinary applications such as medical imaging including stroke MRI/fMRI imaging, real-time cancer imaging. He led and managed significant research programs in developing machine-learning, deep-learning and translational data science models, and software tools to aid the diagnosis and prediction of disease outcomes, particularly for hard-to-manage complex and chronic diseases. His research interest also includes developing Data Science, machine learning and deep learning algorithms, models and software tools utilising different types of data, especially medical images, neuroimaging (MRI, fMRI, Ultrasound, X-Ray), EEG, ECG, Bioinformatics, and secondary usage of routinely collected data.