Invited Speaker 2: Prof. Abir Jaafar Hussain
Affiliation: University of Sharjah; Liverpool John Moores University
Date: September 16, 2026, 11:00 AM
Talk Title: AI Applications in Industry: Innovation, Impact, and Responsible Adoption
Bio: Abir Hussain is a Professor of Image and Signal Processing at the University of Sharjah. She is also a visiting professor with Liverpool John Moores University, where she worked for over 23 years.
She completed her PhD study at the University of Manchester Institute of Science and Technology (UMIST), UK, in 2000 with a thesis titled Polynomial Neural Networks for Image and Signal Processing. She has published numerous refereed research papers in conferences and journals in the areas of neural networks, signal prediction, telecommunication fraud detection, and image compression.
She has worked with higher-order and recurrent neural networks and their applications to financial, physical, e-health, and image-compression techniques. With her research students, she has developed a number of recurrent neural-network architectures. Her research has appeared in highly regarded journals including Expert Systems with Applications, PLOS ONE, Electronics Letters, Neurocomputing, and Neural Computing and Applications.
She is a PhD supervisor and an external examiner for research degrees including PhD and MPhil. She is also one of the initiators and chairs of the Developments in eSystems Engineering series, most notably represented by the IEEE technically sponsored DeSE International Conference Series.
Abstract: Artificial intelligence is making significant changes to industries including finance, healthcare, and agriculture at an unprecedented pace. From intelligent fraud detection, algorithmic risk assessment, and personalized financial services to AI-assisted diagnostics, predictive healthcare, and streamlined clinical operations, AI is unlocking new levels of innovation, efficiency, and value creation.
While these advances offer remarkable benefits, successful AI adoption requires more than technological capability. Organizations must address critical issues surrounding data quality, privacy, transparency, fairness, bias mitigation, explainability, regulatory compliance, and governance. In highly regulated industries such as finance and healthcare, trust remains central to AI deployment. The keynote therefore explores frameworks for responsible AI, emphasizing the importance of human oversight, ethical decision-making, robust risk management, and interdisciplinary collaboration between technology experts, domain specialists, regulators, and business leaders.
This keynote provides details on how organizations are moving beyond experimentation to real-world AI deployment, highlighting practical applications and measurable business outcomes. It also examines the challenges accompanying AI adoption, including transparency, ethical decision-making, and building trust among customers, patients, and professionals.