Speaker: Hani Hagras
Title: Towards True Explainable Artificial Intelligence for Real-World Applications
Time: 10:00 AM, June 25, 2025(Wednesday)
Location: Meeting Room 3, East Library
Abstract:
The recent advances in computing power coupled with the rapid increases in the quantity of available data has led to a resurgence in the theory and applications of Artificial Intelligence (AI). However, the use of complex AI algorithms could result in a lack of transparency to users which is termed as black/opaque box models. Thus, for AI to be trusted and widely used by governments and industries, there is a need for greater transparency through the creation of human friendly explainable AI (XAI) systems. XAI aims to make machines understand the context and environment in which they operate, and over time build underlying explanatory models that allow them to characterize real-world phenomena. The XAI concept provides an explanation of individual decisions, enables understanding of overall strengths and weaknesses, and conveys an understanding of how the system will behave in the future and how to correct the system’s mistakes. In this keynote speech, we will introduce the concepts of XAI by moving towards “explainable AI” (XAI) to achieve a significantly positive impact on communities and industries all over the world and will present novel techniques enabling to deliver human friendly XAI systems which could be easily understood, analysed and augmented by humans. This will allow to the wider deployment of AI systems which are trusted in various real world applications.
Personal Introduction:
Professor Hani Hagras holds the position of Professor of Artificial Intelligence at the University of Essex, UK, concurrently serving as Director of Impact, Director of the Computational Intelligence Centre, and Head of the Artificial Intelligence Research Group. He is a Fellow of IEEE, IET, PFHEA, AIIA, and AAIA. His primary research centers on Explainable AI (XAI) and Data Science, with applications spanning finance, cyber-physical systems, neuroscience, life sciences, intelligent robotics, and industrial process control. Author of over 500 publications and holder of 11 industrial patents in XAI, he ranks among the world's top 2% most-cited scientists (Scopus 2021) and is a globally top-ranked scholar (top 0.05%, ScholarGPS). Professor Hagras has received numerous prestigious awards, including twice the IEEE Transactions on Fuzzy Systems Outstanding Paper Award, multiple IEEE FUZZ Conference Best Paper Awards, the Global Telecommunications Business Award (2015, 2017, with BT), IEEE CIS Distinguished Lecturer (2016), University of Essex Research Impact Award (2017), and awards for knowledge transfer and innovation. He serves as Associate Editor for leading journals like IEEE Transactions on Fuzzy Systems and IEEE Transactions on Artificial Intelligence, and has chaired major IEEE conferences including FUZZ-IEEE.
[Editor: Wanqi Liu]