Applied computational intelligence holds immense potential to revolutionise healthcare by enabling personalised, adaptive, and anticipatory care. However, several challenges must be addressed before these technologies can be widely adopted.
One of the most significant challenges is real-time processing. Many healthcare applications demand systems capable of processing data in real time. However, current computational intelligence systems often struggle to keep pace with the volume and velocity of data generated in these environments. Additionally, the limited size of available datasets poses a challenge. Many computational intelligence models require large datasets for training and validation. However, healthcare datasets are often limited due to privacy concerns and the complexities of collecting patient data. Furthermore, computational intelligence systems typically require extensive data pre-processing before they can be used for training or inference. This can be a substantial barrier to adoption in healthcare settings, where time is often critical.
Despite these challenges, a growing body of research is dedicated to addressing these issues. This talk will delve into these challenges and present our work on solutions that enable real-time data processing, effective utilisation of small datasets, and faster data pre-processing. We will also discuss strategies for tackling other challenges that need to be addressed in the future. These advancements will pave the way for extending the benefits of applied computational intelligence and gen AI to a broader spectrum of healthcare applications.
Prof. Adel Al-Jumaily is a distinguished researcher and educator in the fields of Computational Intelligence and Health Technology. He currently serves as the Associate Head of the School of IT & Engineering at MIT Sydney and holds the esteemed position of Professor of Data Analytics. Renowned for his expertise, he is also a Professor Research Fellow at ENSTA Bretagne, France, and holds adjunct professor positions at the University of Western Australia and Fahad Bin Sultan University.
Dr. Al-Jumaily earned his Ph.D. in Electrical Engineering (AI) and has cultivated a distinguished career spanning over two decades. His research contributions have been instrumental in advancing the fields of applied computational intelligence, humanised computational intelligence technology, health technology, and bio-mechatronic systems. His innovative work leverages the power of machine learning, artificial intelligence, and generative AI tools to develop tailored solutions that address real-world challenges.
Prof. Al-Jumaily's research has garnered significant recognition, with over 6,200 citations and 14 patents, 13 of which were fully sponsored by industry. He has received two prestigious Higher Degree Research Supervision Completion Awards and has successfully supervised over 20 Ph.D. students to completion, along with more than 30 other higher-degree research students. His exceptional contributions have been acknowledged with 6 best paper awards and 27 research achievement prizes.
Beyond his research accomplishments, Dr. Al-Jumaily has also made substantial contributions to the academic community. He has delivered 32 invited talks at conferences and seminars, served as Program Chair at 33 events, and contributed as a member of 124 technical program committees. Furthermore, he has chaired 20 sessions, demonstrating his leadership and expertise in the field.
Dr. Al-Jumaily's broad expertise encompasses both research and teaching, with over 20 years of professional experience. He is a dedicated senior member of the IEEE, serving as Co-Vice Chair of the IEEE Computational Intelligence Chapter (NSW), and actively participates in various other professional committees. His contributions have significantly impacted the advancement of computational intelligence and health technology.