Faculty and Staff

Dr. Issam Kouatli


Issam Kouatli is an assistant professor of information technology. He holds a PhD in Engineering and an MSc in Manufacturing Technology from the University of Birmingham, UK. His research interests are Intelligent Systems, specifically Genetic Fuzzy Systems and its use in decision-making mechanisms and application. He has worked as an IT consultant and director of Multiware Technologies Limited, a British-based  limited company from 1995 till 2001.

Teaching Interests

Research Interests

Selected Publications

Articles in Refereed Journals:

Kouatli, I. (2018). Emotions in the cloud: a framework architecture for managing emotions with an example of emotional intelligence management for cloud computing organisations. International Journal of Work Organisation and Emotion, 9(2), 187-208.

Kouatli, I. (2017). Religion as Apparatus of Ethical Similarity: A Catalyst Toward the Framework of Ethical Behaviors (FEB) in Technical Environment. In Ethics in the Global South (pp. 91-114). Emerald Publishing Limited.

Kouatli, I. (2011). Multivariable Decision Making Process Using the Concept of Genetic Fuzzimetric Technique. ICIC Express Letters, 5(9A).

Kouatli, I. & Khayat H. (2010). FIE: A Generic Decision Making Tool with an Example of CRM Analysis. European Journal of Management, 10(2), 64-72.

Kouatli, I. & Beyrouti, N. (2010). Student Performance Expectation System Using Genetic Fuzzimetric Technique. Review in Business Research, 10(2), 92-98.

Kouatli, I. (2008). Definition and Selection of Fuzzy Sets in Genetic-Fuzzy Systems Using the Concept of Fuzzimetric Arcs.  Kybernetes, 37(1), 166-181.

Kouatli, I. (1994). A Simplified Fuzzy Multivariable Structure in Manufacturing Environment. International Journal of Intelligent Manufacturing, 5(6).

Kouatli, I. & Jones, B. (1991). An Improved Procedure for the Design of Fuzzy Control Systems. International Journal of Machine Tool and Manufacture, 31(1), 107-122. 

Kouatli, I.  & Jones, B.  (1990). A Guide to the Design of Fuzzy Control Systems for Manufacturing Processes. International Journal of Intelligent Manufacturing, 1, 231-244.