Prof. Jonathan M. Garibaldi

IEEE Fellow

University of Nottingham Ningbo China, China

Prof. Jon Garibaldi is currently the Provost of the University of Nottingham Ningbo China, and a member of the University of Nottingham Executive Board (UEB). He is Head of the Intelligent Modelling and Analysis (IMA) Research Group and was a Founding Director of the University of Nottingham Advanced Data Analysis Centre (ADAC). After joining the School of Computer Science University of Nottingham in 2002, he became a full Professor in 2012, and held a variety of administrative roles including Admissions Tutor, Director of Teaching and then Head of School from 2016 to 2023.

His main research interest is in developing intelligent techniques to model human reasoning in uncertain environments, with a particular emphasis on the medical domain. He has particular interest in using non-standard fuzzy sets and systems, such as type-2 fuzzy sets and systems, to model human reasoning processes. He has published over 300 papers in internationally peer-reviewed venues, and has led or participated in a wide range of multi-disciplinary research projects worth over £80M.

He is a Fellow of the IEEE, was the Editor-in-Chief of IEEE Transactions on Fuzzy Systems from Jan 2017 to Dec 2022, and is currently Vice President of Publications of the IEEE CIS Administrative Committee.

Title: Emerging Topics in Fuzzy AI

Abstract: Fuzzy sets and systems are a mature technology, now in existence for almost 60 years, and one of the three main pillars of Computational Intelligence. Whilst fuzzy sets and systems have made significant impact in CI over the years, recently there has been a relative decline in interest, with (particularly) Deep Learning and Large Language Models receiving huge attention worldwide and largely dominating AI research. In this talk, I will argue that fuzzy-based research still has an important role to play in the future of AI. As such, I will identify and discuss some emerging topics in fuzzy systems which I suggest are interesting and potentially valuable areas of future research focus.