Professor Aladdin Ayesh

CITP CEng FBCS, SFHEA

Personal Chair of Artificial Intelligence

Accepting PhDs

51cg

Email Address: aladdin.ayesh@abdn.ac.uk
School/Department: School of Natural and Computing Sciences

Biography

Aladdin Ayesh, MSc (Essex, 1996), PhD (LJMU, 2000), is currently the Vice Dean for Joint Institute of Data Sciences and Artificial Intelligence at 51cg in UK. He also holds a Personal Chair as a Professor of Artificial Intelligence. Prior to his current role, he was a Professor of Artificial Intelligence at De Montfort University. His research focuses on computational cognition, machine learning and explainable AI. His research explored cognitive architectures, emotion modeling and recognition, and applied AI using variety of machine learning techniques including statistical approaches, e.g. Markov Models and Bayesian Networks, logic-based and symbolic approaches, e.g. Modal and Fuzzy Logics, and neural approaches, e.g. Self-Organizing Maps and Deep Learning Classifiers. He applies these techniques in three primary areas: Health Informatics, Sustainable Development, and Data Privacy. Prof. Ayesh has over 150 publications, supervised 24 PhD students to successful completions, and participated in 26 funded projects. He is a founding editor of four international journals and chaired several international conferences. He is also a member of two IEEE technical committees, several IEEE Standards working groups, and a contributor to IEEE 7010-2020 – IEEE Recommended Practice for Assessing the Impact of Autonomous and Intelligent Systems on Human Well-Being.

Memberships and Affiliations

Internal Memberships: School Executive.

Joint Institute Committees.
External Memberships: BCS Fellow

IEEE Senior Member

AHE Senior Fellow

IEEE Transactions on Affective Computing steering committee chair (2019 - 2024)

Research

Research Overview

My research focuses on computational cognition, machine learning and explainable AI. In various research projects, I have explored cognitive architectures, emotion modeling and recognition, and applied AI using variety of machine learning techniques including statistical approaches, e.g. Markov Models and Bayesian Networks, logic-based and symbolic approaches, e.g. Modal and Fuzzy Logics, and neural approaches, e.g. Self-Organizing Maps and Deep Learning Classifiers. My team and I applied these techniques in three primary areas: Health Informatics, Sustainable Development, and Data Privacy.

Research Areas

Accepting PhDs

I am currently accepting PhDs in Computing Science, Artificial Intelligence.

Please get in touch if you would like to discuss your research ideas further.

Email Me

Computing Science

Supervising
Accepting PhDs

View Research Area

Artificial Intelligence

Supervising
Accepting PhDs

View Research Area

Nutrition and Health

Supervising

View Research Area

Applied Health Sciences

Supervising

View Research Area

Research Specialisms

Artificial Intelligence
Machine Learning
Cognitive Modelling
Natural Language Processing
Neural Computing

Our research specialisms are based on the Higher Education Classification of Subjects (HECoS) which is , published under the licence.

Supervision

My current supervision areas are: Computing Science, Artificial Intelligence, Nutrition and Health, Applied Health Sciences.

I have supervised 25 PhD projects to successful completions of which 21 first supervision and 4 second supervision.

I have examined 23 PhD and MPhil projects of which 18 at National Universities: Hull, Essex, Manchester, Edinburgh, Leeds, Leicester, Huddersfield, Liverpool John Moores, and Bradford; and 5 at European Universities of: Le Havre, Rouen, Paris 8, and Granada.

Publications

Update

51cg