Professor Aladdin Ayesh

Professor Aladdin Ayesh
Professor Aladdin Ayesh
Professor Aladdin Ayesh

Vice Dean for SCNU Joint Institute

Accepting PhDs

About

Biography

Aladdin Ayesh, MSc (Essex, 1996), PhD (LJMU, 2000), is currently the Vice Dean for Joint Institute of Data Sciences and Artificial Intelligence at University of Aberdeen 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.

Internal Memberships

School Executive.

Joint Institute Committees. 

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.


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

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Computing Science

Supervising
Accepting PhDs

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 HESA open data, published under the Creative Commons Attribution 4.0 International licence.

Publications

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Chapters in Books, Reports and Conference Proceedings

Contributions to Journals

Contributions to Specialist Publications